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eachadea
/
legacy-vicuna-13b

Text Generation
Transformers
PyTorch
llama
vicuna
text-generation-inference
Model card Files Files and versions
xet
Community
10

Instructions to use eachadea/legacy-vicuna-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eachadea/legacy-vicuna-13b with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="eachadea/legacy-vicuna-13b")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("eachadea/legacy-vicuna-13b")
    model = AutoModelForCausalLM.from_pretrained("eachadea/legacy-vicuna-13b")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use eachadea/legacy-vicuna-13b with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "eachadea/legacy-vicuna-13b"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "eachadea/legacy-vicuna-13b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/eachadea/legacy-vicuna-13b
  • SGLang

    How to use eachadea/legacy-vicuna-13b 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 "eachadea/legacy-vicuna-13b" \
        --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": "eachadea/legacy-vicuna-13b",
    		"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 "eachadea/legacy-vicuna-13b" \
            --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": "eachadea/legacy-vicuna-13b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use eachadea/legacy-vicuna-13b with Docker Model Runner:

    docker model run hf.co/eachadea/legacy-vicuna-13b
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#10 opened over 1 year ago by
SFconvertbot

Adding Evaluation Results

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

Adding Evaluation Results

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

Model taking too much time

#7 opened about 3 years ago by
kanwalkhalid

how to get 30B vicuna

3
#6 opened about 3 years ago by
baby1

what's the origin train data

2
#5 opened about 3 years ago by
baby1

Update README.md

1
#4 opened over 3 years ago by
thawani

OSError: Unable to load weights from pytorch checkpoint file for './vicuna-13b/pytorch_model-00002-of-00003.bin' at

๐Ÿ‘ 1
#3 opened over 3 years ago by
hswu

Tokenizer class LlamaTokenizer does not exist

๐Ÿ‘ 8
8
#2 opened over 3 years ago by
xerxes01
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