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MaAIos
/
Henyo-153M

Text Generation
Transformers
PyTorch
Safetensors
Tagalog
custom_henyo_culturax
custom-architecture
henyo
Model card Files Files and versions
xet
Community
1

Instructions to use MaAIos/Henyo-153M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MaAIos/Henyo-153M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="MaAIos/Henyo-153M")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("MaAIos/Henyo-153M", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use MaAIos/Henyo-153M with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "MaAIos/Henyo-153M"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "MaAIos/Henyo-153M",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/MaAIos/Henyo-153M
  • SGLang

    How to use MaAIos/Henyo-153M 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 "MaAIos/Henyo-153M" \
        --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": "MaAIos/Henyo-153M",
    		"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 "MaAIos/Henyo-153M" \
            --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": "MaAIos/Henyo-153M",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use MaAIos/Henyo-153M with Docker Model Runner:

    docker model run hf.co/MaAIos/Henyo-153M
Henyo-153M
918 MB
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  • 2 contributors
History: 6 commits
marcuscedricridia's picture
marcuscedricridia
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#1)
10e4545 verified 5 months ago
  • .gitattributes
    1.52 kB
    initial commit 5 months ago
  • README.md
    2.03 kB
    Upload README.md with huggingface_hub 5 months ago
  • config.json
    318 Bytes
    Upload model 5 months ago
  • merges.txt
    456 kB
    Upload tokenizer 5 months ago
  • model.safetensors
    456 MB
    xet
    Adding `safetensors` variant of this model (#1) 5 months ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch.FloatStorage",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    456 MB
    xet
    Upload model 5 months ago
  • special_tokens_map.json
    583 Bytes
    Upload tokenizer 5 months ago
  • tokenizer.json
    3.56 MB
    Upload tokenizer 5 months ago
  • tokenizer_config.json
    699 Bytes
    Upload tokenizer 5 months ago
  • train_henyo.py
    5.9 kB
    Upload train_henyo.py with huggingface_hub 5 months ago
  • vocab.json
    798 kB
    Upload tokenizer 5 months ago