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OpenAssistant
/
stablelm-7b-sft-v7-epoch-3

Text Generation
Transformers
PyTorch
English
gpt_neox
sft
text-generation-inference
Model card Files Files and versions
xet
Community
11

Instructions to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="OpenAssistant/stablelm-7b-sft-v7-epoch-3")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("OpenAssistant/stablelm-7b-sft-v7-epoch-3")
    model = AutoModelForCausalLM.from_pretrained("OpenAssistant/stablelm-7b-sft-v7-epoch-3")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "OpenAssistant/stablelm-7b-sft-v7-epoch-3"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "OpenAssistant/stablelm-7b-sft-v7-epoch-3",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/OpenAssistant/stablelm-7b-sft-v7-epoch-3
  • SGLang

    How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "OpenAssistant/stablelm-7b-sft-v7-epoch-3" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "OpenAssistant/stablelm-7b-sft-v7-epoch-3",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "OpenAssistant/stablelm-7b-sft-v7-epoch-3" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "OpenAssistant/stablelm-7b-sft-v7-epoch-3",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use OpenAssistant/stablelm-7b-sft-v7-epoch-3 with Docker Model Runner:

    docker model run hf.co/OpenAssistant/stablelm-7b-sft-v7-epoch-3
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#11 opened over 1 year ago by
SFconvertbot

Adding Evaluation Results

#10 opened over 2 years ago by
leaderboard-pr-bot

[AUTOMATED] Model Memory Requirements

#9 opened over 2 years ago by
model-sizer-bot

The model weights are not tied. Please use the `tie_weights` method before using the `infer_auto_device` function.

1
#8 opened almost 3 years ago by
carlosmoises

GPTQ 4bit 128g

#7 opened about 3 years ago by
pszemraj

3B Model

#6 opened about 3 years ago by
aszfcxcgszdx

GGML f16, q4_0, q4_1, q4_2, q4_3

#4 opened about 3 years ago by
oeathus

Can anyone make ggml 4bit q4_0 version?

3
#3 opened about 3 years ago by
4eJIoBek
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