Text Generation
Transformers
PyTorch
English
qheart
feature-extraction
medical
ecg
question-answering
multimodal
custom_code
Instructions to use Manhph2211/Q-HEART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manhph2211/Q-HEART with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Manhph2211/Q-HEART", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Manhph2211/Q-HEART", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Manhph2211/Q-HEART with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Manhph2211/Q-HEART" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Manhph2211/Q-HEART", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Manhph2211/Q-HEART
- SGLang
How to use Manhph2211/Q-HEART 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 "Manhph2211/Q-HEART" \ --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": "Manhph2211/Q-HEART", "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 "Manhph2211/Q-HEART" \ --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": "Manhph2211/Q-HEART", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Manhph2211/Q-HEART with Docker Model Runner:
docker model run hf.co/Manhph2211/Q-HEART
Update config.json
Browse files- config.json +1 -1
config.json
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@@ -5,7 +5,7 @@
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"AutoConfig": "configuration_qheart.QHEARTConfig",
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"AutoModel": "modeling_qheart.QHEARTForECGQA",
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"AutoModelForCausalLM": "modeling_qheart.QHEARTForECGQA"
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}
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"encoder_layers": 12,
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"encoder_embed_dim": 768,
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"encoder_ffn_embed_dim": 3072,
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"AutoConfig": "configuration_qheart.QHEARTConfig",
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"AutoModel": "modeling_qheart.QHEARTForECGQA",
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"AutoModelForCausalLM": "modeling_qheart.QHEARTForECGQA"
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+
},
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"encoder_layers": 12,
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"encoder_embed_dim": 768,
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"encoder_ffn_embed_dim": 3072,
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