mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
25 lines
757 B
Markdown
25 lines
757 B
Markdown
|
# Predibase
|
||
|
|
||
|
Learn how to use LangChain with models on Predibase.
|
||
|
|
||
|
## Setup
|
||
|
- Create a [Predibase](hhttps://predibase.com/) account and [API key](https://docs.predibase.com/sdk-guide/intro).
|
||
|
- Install the Predibase Python client with `pip install predibase`
|
||
|
- Use your API key to authenticate
|
||
|
|
||
|
### LLM
|
||
|
|
||
|
Predibase integrates with LangChain by implementing LLM module. You can see a short example below or a full notebook under LLM > Integrations > Predibase.
|
||
|
|
||
|
```python
|
||
|
import os
|
||
|
os.environ["PREDIBASE_API_TOKEN"] = "{PREDIBASE_API_TOKEN}"
|
||
|
|
||
|
from langchain.llms import Predibase
|
||
|
|
||
|
model = Predibase(model = 'vicuna-13b', predibase_api_key=os.environ.get('PREDIBASE_API_TOKEN'))
|
||
|
|
||
|
response = model("Can you recommend me a nice dry wine?")
|
||
|
print(response)
|
||
|
```
|