Predibase

Learn how to use LangChain with models on Predibase.

Setup

• Create a Predibase account and API key.
• 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.

import os
os.environ["PREDIBASE_API_TOKEN"] = "{PREDIBASE_API_TOKEN}"

from langchain_community.llms import Predibase

model = Predibase(
    model="mistral-7b",
    predibase_api_key=os.environ.get("PREDIBASE_API_TOKEN"),
    predibase_sdk_version=None,  # optional parameter (defaults to the latest Predibase SDK version if omitted)
)

response = model.invoke("Can you recommend me a nice dry wine?")
print(response)

API Reference:Predibase

Predibase also supports Predibase-hosted and HuggingFace-hosted adapters that are fine-tuned on the base model given by the model argument:

import os
os.environ["PREDIBASE_API_TOKEN"] = "{PREDIBASE_API_TOKEN}"

from langchain_community.llms import Predibase

# The fine-tuned adapter is hosted at Predibase (adapter_version must be specified).
model = Predibase(
    model="mistral-7b",
    predibase_api_key=os.environ.get("PREDIBASE_API_TOKEN"),
    predibase_sdk_version=None,  # optional parameter (defaults to the latest Predibase SDK version if omitted)
    adapter_id="e2e_nlg",
    adapter_version=1,
)

response = model.invoke("Can you recommend me a nice dry wine?")
print(response)

API Reference:Predibase

Predibase also supports adapters that are fine-tuned on the base model given by the model argument:

import os
os.environ["PREDIBASE_API_TOKEN"] = "{PREDIBASE_API_TOKEN}"

from langchain_community.llms import Predibase

# The fine-tuned adapter is hosted at HuggingFace (adapter_version does not apply and will be ignored).
model = Predibase(
    model="mistral-7b",
    predibase_api_key=os.environ.get("PREDIBASE_API_TOKEN"),
    predibase_sdk_version=None,  # optional parameter (defaults to the latest Predibase SDK version if omitted)
    adapter_id="predibase/e2e_nlg",
)

response = model.invoke("Can you recommend me a nice dry wine?")
print(response)

API Reference:Predibase