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NoesisLab
/
Asterisk-135M

Text Generation
Transformers
Safetensors
English
asterisk
aspp
hybrid-architecture
graph-reasoning
sft
trl
conversational
custom_code
Model card Files Files and versions
xet
Community

Instructions to use NoesisLab/Asterisk-135M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NoesisLab/Asterisk-135M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="NoesisLab/Asterisk-135M", trust_remote_code=True)
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("NoesisLab/Asterisk-135M", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use NoesisLab/Asterisk-135M with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "NoesisLab/Asterisk-135M"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "NoesisLab/Asterisk-135M",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/NoesisLab/Asterisk-135M
  • SGLang

    How to use NoesisLab/Asterisk-135M 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 "NoesisLab/Asterisk-135M" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "NoesisLab/Asterisk-135M",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "NoesisLab/Asterisk-135M" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "NoesisLab/Asterisk-135M",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use NoesisLab/Asterisk-135M with Docker Model Runner:

    docker model run hf.co/NoesisLab/Asterisk-135M
Asterisk-135M
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  • 1 contributor
History: 18 commits
OzTianlu's picture
OzTianlu
Update README.md
5bd36fb verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • AsteriskForCausalLM.py
    13.9 kB
    Update AsteriskForCausalLM.py 4 months ago
  • README.md
    9.28 kB
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  • chat_template.jinja
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  • config.json
    1.13 kB
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  • generation_config.json
    142 Bytes
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  • handler.py
    4.57 kB
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  • merges.txt
    466 kB
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  • model.safetensors
    685 MB
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  • requirements.txt
    38 Bytes
    Create requirements.txt 4 months ago
  • special_tokens_map.json
    655 Bytes
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  • tokenizer.json
    3.52 MB
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  • tokenizer_config.json
    3.4 kB
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  • training_args.bin

    Detected Pickle imports (10)

    • "transformers.trainer_utils.HubStrategy",
    • "trl.trainer.sft_config.SFTConfig",
    • "torch.device",
    • "transformers.trainer_utils.SaveStrategy",
    • "transformers.training_args.OptimizerNames",
    • "transformers.trainer_pt_utils.AcceleratorConfig",
    • "transformers.trainer_utils.IntervalStrategy",
    • "transformers.trainer_utils.SchedulerType",
    • "accelerate.utils.dataclasses.DistributedType",
    • "accelerate.state.PartialState"

    How to fix it?

    6.35 kB
    xet
    Upload 12 files 4 months ago
  • vocab.json
    801 kB
    Upload 12 files 4 months ago