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TPreview
/
GaMS3-12B-Lex2

Text Generation
PEFT
Safetensors
Transformers
llama-factory
lora
conversational
Model card Files Files and versions
xet
Community

Instructions to use TPreview/GaMS3-12B-Lex2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use TPreview/GaMS3-12B-Lex2 with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("cjvt/GaMS3-12B")
    model = PeftModel.from_pretrained(base_model, "TPreview/GaMS3-12B-Lex2")
  • Transformers

    How to use TPreview/GaMS3-12B-Lex2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="TPreview/GaMS3-12B-Lex2")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("TPreview/GaMS3-12B-Lex2", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use TPreview/GaMS3-12B-Lex2 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "TPreview/GaMS3-12B-Lex2"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "TPreview/GaMS3-12B-Lex2",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/TPreview/GaMS3-12B-Lex2
  • SGLang

    How to use TPreview/GaMS3-12B-Lex2 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 "TPreview/GaMS3-12B-Lex2" \
        --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": "TPreview/GaMS3-12B-Lex2",
    		"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 "TPreview/GaMS3-12B-Lex2" \
            --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": "TPreview/GaMS3-12B-Lex2",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use TPreview/GaMS3-12B-Lex2 with Docker Model Runner:

    docker model run hf.co/TPreview/GaMS3-12B-Lex2
GaMS3-12B-Lex2 / global_step115
9.35 GB
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  • 1 contributor
History: 1 commit
tknez's picture
tknez
Upload model checkpoint v1
a7e8418 verified 14 days ago
  • bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt
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  • bf16_zero_pp_rank_3_mp_rank_00_optim_states.pt
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  • mp_rank_00_model_states.pt
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