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ylh1013
/
ja_chatbot

Text Generation
Transformers
PyTorch
gpt2
Generated from Trainer
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use ylh1013/ja_chatbot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ylh1013/ja_chatbot with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="ylh1013/ja_chatbot")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMultimodalLM
    
    tokenizer = AutoTokenizer.from_pretrained("ylh1013/ja_chatbot")
    model = AutoModelForMultimodalLM.from_pretrained("ylh1013/ja_chatbot")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use ylh1013/ja_chatbot with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "ylh1013/ja_chatbot"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "ylh1013/ja_chatbot",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/ylh1013/ja_chatbot
  • SGLang

    How to use ylh1013/ja_chatbot 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 "ylh1013/ja_chatbot" \
        --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": "ylh1013/ja_chatbot",
    		"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 "ylh1013/ja_chatbot" \
            --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": "ylh1013/ja_chatbot",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use ylh1013/ja_chatbot with Docker Model Runner:

    docker model run hf.co/ylh1013/ja_chatbot
ja_chatbot
1.37 GB
Ctrl+K
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  • 1 contributor
History: 12 commits
ylh1013's picture
ylh1013
ja_chatbot
8e19ffd over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • .gitignore
    13 Bytes
    Training in progress, epoch 1 over 4 years ago
  • README.md
    1.07 kB
    ja_chatbot over 4 years ago
  • added_tokens.json
    16 Bytes
    Training in progress, epoch 1 over 4 years ago
  • config.json
    957 Bytes
    Training in progress, epoch 1 over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    1.37 GB
    xet
    Training in progress, epoch 1 over 4 years ago
  • special_tokens_map.json
    193 Bytes
    Training in progress, epoch 1 over 4 years ago
  • spiece.model
    806 kB
    xet
    Training in progress, epoch 1 over 4 years ago
  • tokenizer_config.json
    550 Bytes
    Training in progress, epoch 1 over 4 years ago
  • training_args.bin

    Detected Pickle imports (5)

    • "transformers.trainer_utils.HubStrategy",
    • "transformers.trainer_utils.IntervalStrategy",
    • "torch.device",
    • "transformers.training_args.TrainingArguments",
    • "transformers.trainer_utils.SchedulerType"

    How to fix it?

    2.8 kB
    xet
    Training in progress, epoch 1 over 4 years ago