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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Manhph2211/Q-HEART", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
Commit History
-
.
Verified signaturec64523b -
.
Verified signaturee377953
-
.
Verified signature67bb93f
-
.
Verified signature44c94cc
-
Update README.md
Verified signaturebcb94bf
-
Update README.md
Verified signature0f6e94c -
Update README.md
Verified signaturef5a3c5b -
Update modeling_qheart.py
Verified signaturead755f6 -
Update config.json
Verified signature956cef5 -
Update config.json
Verified signaturece056b5 -
,
9ff51b9 -
Update README.md
Verified signature479d233 -
Update README.md
Verified signature5c6c1f6 -
.
fee5c3d -
.
5ad21a6
-
Rename best.bin to sample.bin
Verified signature5883df0 -
Upload best.bin with huggingface_hub
Verified signature4ac90f0
-
Update README.md
Verified signature260ea02 -
Create config.json
Verified signaturebeb0642 -
initial commit
Verified signaturec070929