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techdotus
/
Tokle-3M

Text Generation
Transformers
Safetensors
English
tokle
causal-lm
custom-architecture
slm
small-language-model
spab
custom_code
Model card Files Files and versions
xet
Community

Instructions to use techdotus/Tokle-3M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use techdotus/Tokle-3M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="techdotus/Tokle-3M", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("techdotus/Tokle-3M", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use techdotus/Tokle-3M with vLLM:

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

    How to use techdotus/Tokle-3M 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 "techdotus/Tokle-3M" \
        --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": "techdotus/Tokle-3M",
    		"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 "techdotus/Tokle-3M" \
            --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": "techdotus/Tokle-3M",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use techdotus/Tokle-3M with Docker Model Runner:

    docker model run hf.co/techdotus/Tokle-3M
Tokle-3M
45.9 MB
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  • 1 contributor
History: 6 commits
anandselvadurai-techus's picture
anandselvadurai-techus
Update README.md
0d30b28 verified about 2 hours ago
  • .gitattributes
    1.52 kB
    initial commit about 2 hours ago
  • LICENSE
    1.06 kB
    Initial Commit - Tokle about 2 hours ago
  • README.md
    4.71 kB
    Update README.md about 2 hours ago
  • config.json
    741 Bytes
    Initial Commit - Tokle about 2 hours ago
  • configuration_tokle.py
    2.82 kB
    Initial Commit - Tokle about 2 hours ago
  • generation_config.json
    208 Bytes
    Initial Commit - Tokle about 2 hours ago
  • model.safetensors
    11.6 MB
    xet
    Updated Files. about 2 hours ago
  • modeling_tokle.py
    20.8 kB
    Updated Files. about 2 hours ago
  • spab_table.safetensors
    33.6 MB
    xet
    Updated Files. about 2 hours ago
  • special_tokens_map.json
    414 Bytes
    Initial Commit - Tokle about 2 hours ago
  • tokenizer.json
    455 kB
    Initial Commit - Tokle about 2 hours ago
  • tokenizer_config.json
    187 kB
    Initial Commit - Tokle about 2 hours ago