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oscowlai
/
Wiola13M

Text Generation
Transformers
TensorBoard
Safetensors
PyTorch
English
wiola
transformer
causal-lm
small-language-model
spiral-rope
gated-attention
oscowl
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use oscowlai/Wiola13M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use oscowlai/Wiola13M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="oscowlai/Wiola13M")
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("oscowlai/Wiola13M", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use oscowlai/Wiola13M with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "oscowlai/Wiola13M"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "oscowlai/Wiola13M",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/oscowlai/Wiola13M
  • SGLang

    How to use oscowlai/Wiola13M 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 "oscowlai/Wiola13M" \
        --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": "oscowlai/Wiola13M",
    		"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 "oscowlai/Wiola13M" \
            --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": "oscowlai/Wiola13M",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use oscowlai/Wiola13M with Docker Model Runner:

    docker model run hf.co/oscowlai/Wiola13M
Wiola13M
520 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 3 commits
aryuemaan's picture
aryuemaan
Create README.md
77f303d verified 4 days ago
  • checkpoint-18000
    Release Wiola13M v1.0.0 4 days ago
  • checkpoint-19000
    Release Wiola13M v1.0.0 4 days ago
  • checkpoint-20000
    Release Wiola13M v1.0.0 4 days ago
  • logs
    Release Wiola13M v1.0.0 4 days ago
  • .gitattributes
    1.52 kB
    initial commit 4 days ago
  • README.md
    3.48 kB
    Create README.md 4 days ago
  • config.json
    572 Bytes
    Release Wiola13M v1.0.0 4 days ago
  • generation_config.json
    124 Bytes
    Release Wiola13M v1.0.0 4 days ago
  • model.safetensors
    51.7 MB
    xet
    Release Wiola13M v1.0.0 4 days ago
  • special_tokens_map.json
    552 Bytes
    Release Wiola13M v1.0.0 4 days ago
  • tokenizer.json
    2.26 MB
    Release Wiola13M v1.0.0 4 days ago
  • tokenizer_config.json
    937 Bytes
    Release Wiola13M v1.0.0 4 days ago
  • training_args.bin

    Detected Pickle imports (9)

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

    How to fix it?

    5.18 kB
    xet
    Release Wiola13M v1.0.0 4 days ago