LangChain

抱抱脸（Huggingface）#

抱抱脸（Huggingface） (opens in a new tab)是一个平台，拥有超过120k个模型、20k个数据集和50k个演示应用程序（空间)，所有内容都是开源和公开的，在这个在线平台上，人们可以轻松合作和构建机器学习。

此示例展示了如何连接到抱抱脸（Huggingface）。

要使用，您应该安装了huggingface_hub的python软件包 (opens in a new tab)。

!pip install huggingface_hub > /dev/null

# get a token: https://huggingface.co/docs/api-inference/quicktour#get-your-api-token
 
from getpass import getpass
 
HUGGINGFACEHUB_API_TOKEN = getpass()

import os
os.environ["HUGGINGFACEHUB_API_TOKEN"] = HUGGINGFACEHUB_API_TOKEN

选择模型

from langchain import HuggingFaceHub
 
repo_id = "google/flan-t5-xl" # See https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads for some other options
 
llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature":0, "max_length":64})

from langchain import PromptTemplate, LLMChain
 
template = """Question: {question}
 
Answer: Let's think step by step."""
prompt = PromptTemplate(template=template, input_variables=["question"])
llm_chain = LLMChain(prompt=prompt, llm=llm)
 
question = "Who won the FIFA World Cup in the year 1994? "
 
print(llm_chain.run(question))

示例#

以下是通过抱抱脸（Huggingface）集成可以访问的一些模型示例。

由稳定性AI提供的StableLM#

请参阅稳定性AI (opens in a new tab)的组织页面以获取可用模型列表。

repo_id = "stabilityai/stablelm-tuned-alpha-3b"
# Others include stabilityai/stablelm-base-alpha-3b
# as well as 7B parameter versions

llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature":0, "max_length":64})

# Reuse the prompt and question from above.
llm_chain = LLMChain(prompt=prompt, llm=llm)
print(llm_chain.run(question))

DataBricks的Dolly#

请查看DataBricks (opens in a new tab)组织页面，了解可用模型列表。

from langchain import HuggingFaceHub
 
repo_id = "databricks/dolly-v2-3b"
 
llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature":0, "max_length":64})

# Reuse the prompt and question from above.
llm_chain = LLMChain(prompt=prompt, llm=llm)
print(llm_chain.run(question))

Writer的Camel#

请查看Writer (opens in a new tab)组织页面，了解可用模型列表。

from langchain import HuggingFaceHub
 
repo_id = "Writer/camel-5b-hf" # See https://huggingface.co/Writer for other options
llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature":0, "max_length":64})

# Reuse the prompt and question from above.
llm_chain = LLMChain(prompt=prompt, llm=llm)
print(llm_chain.run(question))

还有更多！

Gpt4all Huggingface Pipelines