mirror of https://github.com/xtekky/gpt4free
~ | Update Vercel Provider
abc
9 months ago
parent
7875661332
commit
d4acc23c0b
@ -1,289 +1,369 @@
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from __future__ import annotations
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from curl_cffi.requests import AsyncSession
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from __future__ import annotations
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from ..typing import Any, TypedDict
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from .base_provider import AsyncProvider
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import json, base64, requests, execjs, random, uuid
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from ..typing import Any, TypedDict, CreateResult
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from .base_provider import BaseProvider
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from abc import abstractmethod
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class Vercel(AsyncProvider):
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url = "https://sdk.vercel.ai"
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working = False
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class Vercel(BaseProvider):
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url = 'https://sdk.vercel.ai'
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working = True
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supports_gpt_35_turbo = True
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model = "replicate:replicate/llama-2-70b-chat"
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supports_stream = True
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@classmethod
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async def create_async(
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cls,
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@staticmethod
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@abstractmethod
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def create_completion(
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model: str,
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messages: list[dict[str, str]],
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proxy: str = None,
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**kwargs
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) -> str:
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return
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stream: bool, **kwargs ) -> CreateResult:
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headers = {
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'authority' : 'sdk.vercel.ai',
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'accept' : '*/*',
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'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
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'cache-control' : 'no-cache',
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'content-type' : 'application/json',
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'custom-encoding' : AntiBotToken(),
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'origin' : 'https://sdk.vercel.ai',
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'pragma' : 'no-cache',
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'referer' : 'https://sdk.vercel.ai/',
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'sec-ch-ua' : '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
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'sec-ch-ua-mobile' : '?0',
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'sec-ch-ua-platform': '"macOS"',
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'sec-fetch-dest' : 'empty',
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'sec-fetch-mode' : 'cors',
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'sec-fetch-site' : 'same-origin',
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'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.%s.%s Safari/537.36' % (
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random.randint(99, 999),
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random.randint(99, 999)
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)
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}
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json_data = {
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'model' : model_info[model]['id'],
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'messages' : messages,
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'playgroundId': str(uuid.uuid4()),
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'chatIndex' : 0} | model_info[model]['default_params']
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server_error = True
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while server_error:
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response = requests.post('https://sdk.vercel.ai/api/generate',
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headers=headers, json=json_data, stream=True)
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for token in response.iter_content(chunk_size=2046):
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if token != b'Internal Server Error':
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server_error = False
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yield (token.decode())
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def AntiBotToken() -> str:
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headers = {
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'authority' : 'sdk.vercel.ai',
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'accept' : '*/*',
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'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
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'cache-control' : 'no-cache',
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'pragma' : 'no-cache',
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'referer' : 'https://sdk.vercel.ai/',
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'sec-ch-ua' : '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
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'sec-ch-ua-mobile' : '?0',
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'sec-ch-ua-platform': '"macOS"',
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'sec-fetch-dest' : 'empty',
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'sec-fetch-mode' : 'cors',
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'sec-fetch-site' : 'same-origin',
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'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.%s.%s Safari/537.36' % (
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random.randint(99, 999),
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random.randint(99, 999)
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)
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}
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response = requests.get('https://sdk.vercel.ai/openai.jpeg',
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headers=headers).text
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raw_data = json.loads(base64.b64decode(response,
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validate=True))
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js_script = '''const globalThis={marker:"mark"};String.prototype.fontcolor=function(){return `<font>${this}</font>`};
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return (%s)(%s)''' % (raw_data['c'], raw_data['a'])
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raw_token = json.dumps({'r': execjs.compile(js_script).call(''), 't': raw_data['t']},
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separators = (",", ":"))
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return base64.b64encode(raw_token.encode('utf-16le')).decode()
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class ModelInfo(TypedDict):
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id: str
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default_params: dict[str, Any]
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model_info: dict[str, ModelInfo] = {
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"anthropic:claude-instant-v1": {
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"id": "anthropic:claude-instant-v1",
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"default_params": {
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"temperature": 1,
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"maxTokens": 200,
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"topP": 1,
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"topK": 1,
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"presencePenalty": 1,
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"frequencyPenalty": 1,
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"stopSequences": ["\n\nHuman:"],
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'claude-instant-v1': {
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'id': 'anthropic:claude-instant-v1',
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'default_params': {
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'temperature': 1,
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'maximumLength': 1024,
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'topP': 1,
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'topK': 1,
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'presencePenalty': 1,
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'frequencyPenalty': 1,
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'stopSequences': ['\n\nHuman:'],
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},
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},
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"anthropic:claude-v1": {
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"id": "anthropic:claude-v1",
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"default_params": {
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"temperature": 1,
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"maxTokens": 200,
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"topP": 1,
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"topK": 1,
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"presencePenalty": 1,
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"frequencyPenalty": 1,
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"stopSequences": ["\n\nHuman:"],
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'claude-v1': {
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'id': 'anthropic:claude-v1',
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'default_params': {
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'temperature': 1,
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'maximumLength': 1024,
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'topP': 1,
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'topK': 1,
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'presencePenalty': 1,
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'frequencyPenalty': 1,
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'stopSequences': ['\n\nHuman:'],
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},
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},
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"anthropic:claude-v2": {
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"id": "anthropic:claude-v2",
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"default_params": {
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"temperature": 1,
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"maxTokens": 200,
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"topP": 1,
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"topK": 1,
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"presencePenalty": 1,
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"frequencyPenalty": 1,
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"stopSequences": ["\n\nHuman:"],
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'claude-v2': {
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'id': 'anthropic:claude-v2',
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'default_params': {
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'temperature': 1,
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'maximumLength': 1024,
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'topP': 1,
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'topK': 1,
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'presencePenalty': 1,
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'frequencyPenalty': 1,
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'stopSequences': ['\n\nHuman:'],
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},
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},
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"replicate:a16z-infra/llama7b-v2-chat": {
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"id": "replicate:a16z-infra/llama7b-v2-chat",
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"default_params": {
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"temperature": 0.75,
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"maxTokens": 500,
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"topP": 1,
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"repetitionPenalty": 1,
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'a16z-infra/llama7b-v2-chat': {
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'id': 'replicate:a16z-infra/llama7b-v2-chat',
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'default_params': {
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'temperature': 0.75,
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'maximumLength': 3000,
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'topP': 1,
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'repetitionPenalty': 1,
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},
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},
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"replicate:a16z-infra/llama13b-v2-chat": {
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"id": "replicate:a16z-infra/llama13b-v2-chat",
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"default_params": {
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"temperature": 0.75,
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"maxTokens": 500,
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"topP": 1,
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"repetitionPenalty": 1,
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'a16z-infra/llama13b-v2-chat': {
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'id': 'replicate:a16z-infra/llama13b-v2-chat',
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'default_params': {
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'temperature': 0.75,
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'maximumLength': 3000,
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'topP': 1,
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'repetitionPenalty': 1,
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},
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},
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"replicate:replicate/llama-2-70b-chat": {
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"id": "replicate:replicate/llama-2-70b-chat",
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"default_params": {
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"temperature": 0.75,
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"maxTokens": 1000,
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"topP": 1,
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"repetitionPenalty": 1,
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'replicate/llama-2-70b-chat': {
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'id': 'replicate:replicate/llama-2-70b-chat',
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'default_params': {
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'temperature': 0.75,
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'maximumLength': 3000,
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'topP': 1,
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'repetitionPenalty': 1,
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},
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},
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"huggingface:bigscience/bloom": {
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"id": "huggingface:bigscience/bloom",
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"default_params": {
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"temperature": 0.5,
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"maxTokens": 200,
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"topP": 0.95,
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"topK": 4,
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"repetitionPenalty": 1.03,
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'bigscience/bloom': {
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'id': 'huggingface:bigscience/bloom',
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'default_params': {
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'temperature': 0.5,
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'maximumLength': 1024,
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'topP': 0.95,
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'topK': 4,
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'repetitionPenalty': 1.03,
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},
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},
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"huggingface:google/flan-t5-xxl": {
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"id": "huggingface:google/flan-t5-xxl",
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"default_params": {
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"temperature": 0.5,
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"maxTokens": 200,
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"topP": 0.95,
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"topK": 4,
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"repetitionPenalty": 1.03,
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'google/flan-t5-xxl': {
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'id': 'huggingface:google/flan-t5-xxl',
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'default_params': {
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'temperature': 0.5,
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'maximumLength': 1024,
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'topP': 0.95,
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'topK': 4,
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'repetitionPenalty': 1.03,
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},
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},
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"huggingface:EleutherAI/gpt-neox-20b": {
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"id": "huggingface:EleutherAI/gpt-neox-20b",
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"default_params": {
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"temperature": 0.5,
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"maxTokens": 200,
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"topP": 0.95,
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"topK": 4,
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"repetitionPenalty": 1.03,
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"stopSequences": [],
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'EleutherAI/gpt-neox-20b': {
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'id': 'huggingface:EleutherAI/gpt-neox-20b',
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'default_params': {
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'temperature': 0.5,
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'maximumLength': 1024,
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'topP': 0.95,
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'topK': 4,
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'repetitionPenalty': 1.03,
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'stopSequences': [],
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},
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},
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"huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5": {
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"id": "huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
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"default_params": {"maxTokens": 200, "typicalP": 0.2, "repetitionPenalty": 1},
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'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5': {
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'id': 'huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
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'default_params': {
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'maximumLength': 1024,
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'typicalP': 0.2,
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'repetitionPenalty': 1,
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},
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},
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"huggingface:OpenAssistant/oasst-sft-1-pythia-12b": {
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"id": "huggingface:OpenAssistant/oasst-sft-1-pythia-12b",
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"default_params": {"maxTokens": 200, "typicalP": 0.2, "repetitionPenalty": 1},
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'OpenAssistant/oasst-sft-1-pythia-12b': {
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'id': 'huggingface:OpenAssistant/oasst-sft-1-pythia-12b',
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'default_params': {
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'maximumLength': 1024,
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'typicalP': 0.2,
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'repetitionPenalty': 1,
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},
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},
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"huggingface:bigcode/santacoder": {
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"id": "huggingface:bigcode/santacoder",
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"default_params": {
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"temperature": 0.5,
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"maxTokens": 200,
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"topP": 0.95,
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"topK": 4,
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"repetitionPenalty": 1.03,
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'bigcode/santacoder': {
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'id': 'huggingface:bigcode/santacoder',
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'default_params': {
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'temperature': 0.5,
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'maximumLength': 1024,
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'topP': 0.95,
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'topK': 4,
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'repetitionPenalty': 1.03,
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},
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},
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"cohere:command-light-nightly": {
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"id": "cohere:command-light-nightly",
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"default_params": {
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"temperature": 0.9,
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"maxTokens": 200,
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"topP": 1,
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"topK": 0,
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"presencePenalty": 0,
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"frequencyPenalty": 0,
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"stopSequences": [],
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'command-light-nightly': {
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'id': 'cohere:command-light-nightly',
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'default_params': {
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'temperature': 0.9,
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'maximumLength': 1024,
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'topP': 1,
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'topK': 0,
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'presencePenalty': 0,
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'frequencyPenalty': 0,
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'stopSequences': [],
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},
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},
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"cohere:command-nightly": {
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"id": "cohere:command-nightly",
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"default_params": {
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"temperature": 0.9,
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"maxTokens": 200,
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"topP": 1,
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"topK": 0,
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"presencePenalty": 0,
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"frequencyPenalty": 0,
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"stopSequences": [],
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'command-nightly': {
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'id': 'cohere:command-nightly',
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'default_params': {
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'temperature': 0.9,
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'maximumLength': 1024,
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'topP': 1,
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'topK': 0,
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'presencePenalty': 0,
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'frequencyPenalty': 0,
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'stopSequences': [],
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},
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},
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"openai:gpt-4": {
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"id": "openai:gpt-4",
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"default_params": {
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"temperature": 0.7,
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"maxTokens": 500,
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"topP": 1,
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"presencePenalty": 0,
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"frequencyPenalty": 0,
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"stopSequences": [],
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'gpt-4': {
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'id': 'openai:gpt-4',
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'default_params': {
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'temperature': 0.7,
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'maximumLength': 8192,
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'topP': 1,
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'presencePenalty': 0,
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'frequencyPenalty': 0,
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'stopSequences': [],
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},
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},
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"openai:gpt-4-0613": {
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"id": "openai:gpt-4-0613",
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"default_params": {
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"temperature": 0.7,
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"maxTokens": 500,
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"topP": 1,
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"presencePenalty": 0,
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"frequencyPenalty": 0,
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"stopSequences": [],
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'gpt-4-0613': {
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'id': 'openai:gpt-4-0613',
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'default_params': {
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'temperature': 0.7,
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'maximumLength': 8192,
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'topP': 1,
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'presencePenalty': 0,
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'frequencyPenalty': 0,
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'stopSequences': [],
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},
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},
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"openai:code-davinci-002": {
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"id": "openai:code-davinci-002",
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"default_params": {
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"temperature": 0.5,
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"maxTokens": 200,
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"topP": 1,
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"presencePenalty": 0,
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"frequencyPenalty": 0,
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"stopSequences": [],
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'code-davinci-002': {
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'id': 'openai:code-davinci-002',
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'default_params': {
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'temperature': 0.5,
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'maximumLength': 1024,
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'topP': 1,
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'presencePenalty': 0,
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'frequencyPenalty': 0,
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'stopSequences': [],
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},
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},
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"openai:gpt-3.5-turbo": {
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"id": "openai:gpt-3.5-turbo",
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"default_params": {
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"temperature": 0.7,
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"maxTokens": 500,
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"topP": 1,
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"topK": 1,
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"presencePenalty": 1,
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"frequencyPenalty": 1,
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"stopSequences": [],
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'gpt-3.5-turbo': {
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'id': 'openai:gpt-3.5-turbo',
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'default_params': {
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'temperature': 0.7,
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'maximumLength': 4096,
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'topP': 1,
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'topK': 1,
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'presencePenalty': 1,
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'frequencyPenalty': 1,
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'stopSequences': [],
|
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}
|
||||
|
||||
Loading…
Reference in New Issue