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MustEr
/
best_model_for_identifying_frogs

Text Generation
Transformers
PyTorch
google-tensorflow TensorFlow
English
opt
image-generation
frogs
image-recognition
text-generation-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use MustEr/best_model_for_identifying_frogs with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="MustEr/best_model_for_identifying_frogs")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("MustEr/best_model_for_identifying_frogs")
    model = AutoModelForCausalLM.from_pretrained("MustEr/best_model_for_identifying_frogs")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use MustEr/best_model_for_identifying_frogs with vLLM:

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

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

    How to use MustEr/best_model_for_identifying_frogs with Docker Model Runner:

    docker model run hf.co/MustEr/best_model_for_identifying_frogs
best_model_for_identifying_frogs
84.5 MB
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  • 1 contributor
History: 53 commits

This model has 3 files scanned as unsafe.

MustEr's picture
MustEr
Update README.md
b5f7f78 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • LICENSE.md
    11.1 kB
    LEAP - First try about 2 years ago
  • README.md
    3.89 kB
    Update README.md about 2 years ago
  • bg_powned.png
    605 kB
    Upload bg_powned.png about 2 years ago
  • cat.txt
    703 kB
    Work NOWWWWW it is an order about 2 years ago
  • config.json
    651 Bytes
    LEAP - First try about 2 years ago
  • generation_config.json
    137 Bytes
    LEAP - First try about 2 years ago
  • logo.png
    55.3 kB
    Logo about 2 years ago
  • merges.txt
    456 kB
    LEAP - First try about 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    How to fix it?

    47.4 MB
    xet
    Quicker Powning about 2 years ago
  • special_tokens_map.json
    441 Bytes
    LEAP - First try about 2 years ago
  • sub_model.h5
    17.2 MB
    xet
    New strategy: about 2 years ago
  • tf_model.h5
    17.2 MB
    xet
    Locally about 2 years ago
  • tokenizer_config.json
    685 Bytes
    LEAP - First try about 2 years ago
  • vocab.json
    899 kB
    LEAP - First try about 2 years ago