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thrunlab
/
sparse_mistral_50p_no_adapter

Text Generation
Transformers
Safetensors
sparse_mistral
Generated from Trainer
custom_code
Model card Files Files and versions
xet
Community

Instructions to use thrunlab/sparse_mistral_50p_no_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use thrunlab/sparse_mistral_50p_no_adapter with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="thrunlab/sparse_mistral_50p_no_adapter", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("thrunlab/sparse_mistral_50p_no_adapter", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use thrunlab/sparse_mistral_50p_no_adapter with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "thrunlab/sparse_mistral_50p_no_adapter"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "thrunlab/sparse_mistral_50p_no_adapter",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/thrunlab/sparse_mistral_50p_no_adapter
  • SGLang

    How to use thrunlab/sparse_mistral_50p_no_adapter 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 "thrunlab/sparse_mistral_50p_no_adapter" \
        --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": "thrunlab/sparse_mistral_50p_no_adapter",
    		"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 "thrunlab/sparse_mistral_50p_no_adapter" \
            --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": "thrunlab/sparse_mistral_50p_no_adapter",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use thrunlab/sparse_mistral_50p_no_adapter with Docker Model Runner:

    docker model run hf.co/thrunlab/sparse_mistral_50p_no_adapter
sparse_mistral_50p_no_adapter
14.5 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
vxbrandon's picture
vxbrandon
End of training
3948f9d verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    946 Bytes
    End of training about 2 years ago
  • config.json
    1.79 kB
    End of training about 2 years ago
  • generation_config.json
    111 Bytes
    End of training about 2 years ago
  • model-00001-of-00003.safetensors
    4.94 GB
    xet
    End of training about 2 years ago
  • model-00002-of-00003.safetensors
    5 GB
    xet
    End of training about 2 years ago
  • model-00003-of-00003.safetensors
    4.54 GB
    xet
    End of training about 2 years ago
  • model.safetensors.index.json
    24 kB
    End of training about 2 years ago
  • sparsification_sftt.py
    35.6 kB
    End of training about 2 years ago
  • special_tokens_map.json
    551 Bytes
    End of training about 2 years ago
  • tokenizer.json
    1.8 MB
    End of training about 2 years ago
  • tokenizer_config.json
    969 Bytes
    End of training about 2 years ago
  • training_args.bin

    Detected Pickle imports (8)

    • "torch.device",
    • "accelerate.utils.dataclasses.DistributedType",
    • "transformers.trainer_utils.HubStrategy",
    • "transformers.trainer_utils.IntervalStrategy",
    • "transformers.trainer_utils.SchedulerType",
    • "transformers.training_args.TrainingArguments",
    • "accelerate.state.PartialState",
    • "transformers.training_args.OptimizerNames"

    How to fix it?

    4.73 kB
    xet
    End of training about 2 years ago