Text Generation
Transformers
TensorBoard
Safetensors
llama
Generated from Trainer
text-generation-inference
Instructions to use WilliamHH/Assignment2-modified-V4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WilliamHH/Assignment2-modified-V4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="WilliamHH/Assignment2-modified-V4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("WilliamHH/Assignment2-modified-V4") model = AutoModelForCausalLM.from_pretrained("WilliamHH/Assignment2-modified-V4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use WilliamHH/Assignment2-modified-V4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "WilliamHH/Assignment2-modified-V4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WilliamHH/Assignment2-modified-V4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/WilliamHH/Assignment2-modified-V4
- SGLang
How to use WilliamHH/Assignment2-modified-V4 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 "WilliamHH/Assignment2-modified-V4" \ --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": "WilliamHH/Assignment2-modified-V4", "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 "WilliamHH/Assignment2-modified-V4" \ --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": "WilliamHH/Assignment2-modified-V4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use WilliamHH/Assignment2-modified-V4 with Docker Model Runner:
docker model run hf.co/WilliamHH/Assignment2-modified-V4
Commit History
-
Training in progress, step 5625
Verified signaturecefbfdb -
Training in progress, step 5500
Verified signature9bad02a -
Training in progress, step 5000
Verified signaturec764569 -
Training in progress, step 4500
Verified signature9ecf59c -
Training in progress, step 4000
Verified signature3650084 -
Training in progress, step 3500
Verified signature3fafa9a -
Training in progress, step 3000
Verified signature2b82e4c -
Training in progress, step 2500
Verified signaturee49f9d3 -
Training in progress, step 2000
Verified signaturee1d2a8d -
Training in progress, step 1500
Verified signaturebae8397 -
Training in progress, step 1000
Verified signatureac903b9 -
Training in progress, step 500
Verified signature4fbfce4