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pixelsandpointers
/
dialoGPT-small-empatheticdialogues-generation

Text Generation
Transformers
PyTorch
TensorBoard
English
gpt2
conversational
text-generation-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use pixelsandpointers/dialoGPT-small-empatheticdialogues-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use pixelsandpointers/dialoGPT-small-empatheticdialogues-generation with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="pixelsandpointers/dialoGPT-small-empatheticdialogues-generation")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("pixelsandpointers/dialoGPT-small-empatheticdialogues-generation")
    model = AutoModelForCausalLM.from_pretrained("pixelsandpointers/dialoGPT-small-empatheticdialogues-generation")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use pixelsandpointers/dialoGPT-small-empatheticdialogues-generation with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "pixelsandpointers/dialoGPT-small-empatheticdialogues-generation"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "pixelsandpointers/dialoGPT-small-empatheticdialogues-generation",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/pixelsandpointers/dialoGPT-small-empatheticdialogues-generation
  • SGLang

    How to use pixelsandpointers/dialoGPT-small-empatheticdialogues-generation 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 "pixelsandpointers/dialoGPT-small-empatheticdialogues-generation" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "pixelsandpointers/dialoGPT-small-empatheticdialogues-generation",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    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 "pixelsandpointers/dialoGPT-small-empatheticdialogues-generation" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "pixelsandpointers/dialoGPT-small-empatheticdialogues-generation",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use pixelsandpointers/dialoGPT-small-empatheticdialogues-generation with Docker Model Runner:

    docker model run hf.co/pixelsandpointers/dialoGPT-small-empatheticdialogues-generation
dialoGPT-small-empatheticdialogues-generation
513 MB
Ctrl+K
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  • 1 contributor
History: 28 commits
Benjamin Beilharz
Update README.md
4a8d404 over 4 years ago
  • runs
    Training in progress, step 5000 over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 500 over 4 years ago
  • README.md
    180 Bytes
    Update README.md over 4 years ago
  • added_tokens.json
    16 Bytes
    Training in progress, step 500 over 4 years ago
  • config.json
    942 Bytes
    add model over 4 years ago
  • merges.txt
    456 kB
    Training in progress, step 500 over 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    510 MB
    xet
    add model over 4 years ago
  • special_tokens_map.json
    379 Bytes
    Training in progress, step 500 over 4 years ago
  • tokenizer.json
    1.36 MB
    Training in progress, step 500 over 4 years ago
  • tokenizer_config.json
    655 Bytes
    add tokenizer 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?

    3.06 kB
    xet
    Training in progress, step 500 over 4 years ago
  • vocab.json
    798 kB
    Training in progress, step 500 over 4 years ago