Predibase

了解如何在Predibase上使用LangChain与模型。

设置

• 创建一个Predibase账户并获取API密钥。
• 使用 pip install predibase 安装Predibase Python客户端
• 使用您的API密钥进行身份验证

LLM

Predibase 通过实现 LLM 模块与 LangChain 进行集成。你可以查看下面的简短示例，或者在 LLM > 集成 > Predibase 下查看完整的笔记本。

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)
    """
    Optionally use `model_kwargs` to set new default "generate()" settings.  For example:
    {
        "api_token": os.environ.get("HUGGING_FACE_HUB_TOKEN"),
        "max_new_tokens": 5,  # default is 256
    }
    """
    **model_kwargs,
)

"""
Optionally use `kwargs` to dynamically overwrite "generate()" settings.  For example:
{
    "temperature": 0.5,  # default is the value in model_kwargs or 0.1 (initialization default)
    "max_new_tokens": 1024,  # default is the value in model_kwargs or 256 (initialization default)
}
"""
response = model.invoke("Can you recommend me a nice dry wine?", **kwargs)
print(response)

API 参考：Predibase

Predibase 还支持基于 model 参数给定的基础模型进行微调的 Predibase 托管和 HuggingFace 托管适集成：

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,
    """
    Optionally use `model_kwargs` to set new default "generate()" settings.  For example:
    {
        "api_token": os.environ.get("HUGGING_FACE_HUB_TOKEN"),
        "max_new_tokens": 5,  # default is 256
    }
    """
    **model_kwargs,
)

"""
Optionally use `kwargs` to dynamically overwrite "generate()" settings.  For example:
{
    "temperature": 0.5,  # default is the value in model_kwargs or 0.1 (initialization default)
    "max_new_tokens": 1024,  # default is the value in model_kwargs or 256 (initialization default)
}
"""
response = model.invoke("Can you recommend me a nice dry wine?", **kwargs)
print(response)

API 参考：Predibase

Predibase 还支持通过 model 参数指定的基础模型进行微调的适集成：

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",
    """
    Optionally use `model_kwargs` to set new default "generate()" settings.  For example:
    {
        "api_token": os.environ.get("HUGGING_FACE_HUB_TOKEN"),
        "max_new_tokens": 5,  # default is 256
    }
    """
    **model_kwargs,
)

"""
Optionally use `kwargs` to dynamically overwrite "generate()" settings.  For example:
{
    "temperature": 0.5,  # default is the value in model_kwargs or 0.1 (initialization default)
    "max_new_tokens": 1024,  # default is the value in model_kwargs or 256 (initialization default)
}
"""
response = model.invoke("Can you recommend me a nice dry wine?", **kwargs)
print(response)

API 参考：Predibase