mirror of
https://github.com/hwchase17/langchain
synced 2024-10-29 17:07:25 +00:00
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
"""Test HuggingFace Pipeline wrapper."""
|
|
|
|
from pathlib import Path
|
|
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
|
|
|
|
from langchain.llms.huggingface_pipeline import HuggingFacePipeline
|
|
from langchain.llms.loading import load_llm
|
|
from tests.integration_tests.llms.utils import assert_llm_equality
|
|
|
|
|
|
def test_huggingface_pipeline_text_generation() -> None:
|
|
"""Test valid call to HuggingFace text generation model."""
|
|
llm = HuggingFacePipeline.from_model_id(
|
|
model_id="gpt2", task="text-generation", model_kwargs={"max_new_tokens": 10}
|
|
)
|
|
output = llm("Say foo:")
|
|
assert isinstance(output, str)
|
|
|
|
|
|
def test_huggingface_pipeline_text2text_generation() -> None:
|
|
"""Test valid call to HuggingFace text2text generation model."""
|
|
llm = HuggingFacePipeline.from_model_id(
|
|
model_id="google/flan-t5-small", task="text2text-generation"
|
|
)
|
|
output = llm("Say foo:")
|
|
assert isinstance(output, str)
|
|
|
|
|
|
def test_saving_loading_llm(tmp_path: Path) -> None:
|
|
"""Test saving/loading an HuggingFaceHub LLM."""
|
|
llm = HuggingFacePipeline.from_model_id(
|
|
model_id="gpt2", task="text-generation", model_kwargs={"max_new_tokens": 10}
|
|
)
|
|
llm.save(file_path=tmp_path / "hf.yaml")
|
|
loaded_llm = load_llm(tmp_path / "hf.yaml")
|
|
assert_llm_equality(llm, loaded_llm)
|
|
|
|
|
|
def test_init_with_pipeline() -> None:
|
|
"""Test initialization with a HF pipeline."""
|
|
model_id = "gpt2"
|
|
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
|
model = AutoModelForCausalLM.from_pretrained(model_id)
|
|
pipe = pipeline(
|
|
"text-generation", model=model, tokenizer=tokenizer, max_new_tokens=10
|
|
)
|
|
llm = HuggingFacePipeline(pipeline=pipe)
|
|
output = llm("Say foo:")
|
|
assert isinstance(output, str)
|