Instructions to use osidenna/SoftwareReq-DialoGPT-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osidenna/SoftwareReq-DialoGPT-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="osidenna/SoftwareReq-DialoGPT-medium") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("osidenna/SoftwareReq-DialoGPT-medium") model = AutoModelForCausalLM.from_pretrained("osidenna/SoftwareReq-DialoGPT-medium") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use osidenna/SoftwareReq-DialoGPT-medium with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "osidenna/SoftwareReq-DialoGPT-medium" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "osidenna/SoftwareReq-DialoGPT-medium", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/osidenna/SoftwareReq-DialoGPT-medium
- SGLang
How to use osidenna/SoftwareReq-DialoGPT-medium 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 "osidenna/SoftwareReq-DialoGPT-medium" \ --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": "osidenna/SoftwareReq-DialoGPT-medium", "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 "osidenna/SoftwareReq-DialoGPT-medium" \ --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": "osidenna/SoftwareReq-DialoGPT-medium", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use osidenna/SoftwareReq-DialoGPT-medium with Docker Model Runner:
docker model run hf.co/osidenna/SoftwareReq-DialoGPT-medium
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.053390282968499736, | |
| "global_step": 500, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.05, | |
| "learning_rate": 5e-05, | |
| "loss": 0.7848, | |
| "step": 500 | |
| } | |
| ], | |
| "max_steps": 28095, | |
| "num_train_epochs": 3, | |
| "total_flos": 216757291008000.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |