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e34b5f0119
Closes https://github.com/go-skynet/LocalAI/issues/1066 and https://github.com/go-skynet/LocalAI/issues/1065 Standardizes all `examples/`: - Models in one place (other than `rwkv`, which was one-offy) - Env files as `.env.example` with `cp` - Also standardizes comments and links docs |
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docker-compose.yml | ||
models | ||
README.md |
Data query example
Example of integration with HuggingFace Inference API with help of langchaingo.
Setup
Download the LocalAI and start the API:
# Clone LocalAI
git clone https://github.com/go-skynet/LocalAI
cd LocalAI/examples/langchain-huggingface
docker-compose up -d
Node: Ensure you've set HUGGINGFACEHUB_API_TOKEN
environment variable, you can generate it
on Settings / Access Tokens page of HuggingFace site.
This is an example .env
file for LocalAI:
MODELS_PATH=/models
CONTEXT_SIZE=512
HUGGINGFACEHUB_API_TOKEN=hg_123456
Using remote models
Now you can use any remote models available via HuggingFace API, for example let's enable using of
gpt2 model in gpt-3.5-turbo.yaml
config:
name: gpt-3.5-turbo
parameters:
model: gpt2
top_k: 80
temperature: 0.2
top_p: 0.7
context_size: 1024
backend: "langchain-huggingface"
stopwords:
- "HUMAN:"
- "GPT:"
roles:
user: " "
system: " "
template:
completion: completion
chat: gpt4all
Here is you can see in field parameters.model
equal gpt2
and backend
equal langchain-huggingface
.
How to use
# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models
# {"object":"list","data":[{"id":"gpt-3.5-turbo","object":"model"}]}
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
"model": "gpt-3.5-turbo",
"prompt": "A long time ago in a galaxy far, far away",
"temperature": 0.7
}'