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dipta007
/
dagger-4B_SFT_GRPO

Text Generation
Transformers
Safetensors
Bengali
English
math
reasoning
computational-graph
bangla
low-resource
distractor-aware
small-model
Model card Files Files and versions
xet
Community
1

Instructions to use dipta007/dagger-4B_SFT_GRPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use dipta007/dagger-4B_SFT_GRPO with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="dipta007/dagger-4B_SFT_GRPO")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("dipta007/dagger-4B_SFT_GRPO", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use dipta007/dagger-4B_SFT_GRPO with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "dipta007/dagger-4B_SFT_GRPO"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "dipta007/dagger-4B_SFT_GRPO",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/dipta007/dagger-4B_SFT_GRPO
  • SGLang

    How to use dipta007/dagger-4B_SFT_GRPO 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 "dipta007/dagger-4B_SFT_GRPO" \
        --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": "dipta007/dagger-4B_SFT_GRPO",
    		"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 "dipta007/dagger-4B_SFT_GRPO" \
            --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": "dipta007/dagger-4B_SFT_GRPO",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use dipta007/dagger-4B_SFT_GRPO with Docker Model Runner:

    docker model run hf.co/dipta007/dagger-4B_SFT_GRPO
dagger-4B_SFT_GRPO
8.64 GB
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  • 2 contributors
History: 4 commits
dipta007's picture
dipta007
zabir-nabil's picture
zabir-nabil
updated readme (#1)
39bf741 verified 5 months ago
  • .gitattributes
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  • README.md
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  • config.json
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  • model-00001-of-00002.safetensors
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  • model.safetensors.index.json
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  • preprocessor_config.json
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  • processor_config.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer.model
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  • tokenizer_config.json
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