Text Generation
Transformers
TensorBoard
Safetensors
llama
Generated from Trainer
trl
sft
text-generation-inference
Instructions to use neelrr/HW2-supervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neelrr/HW2-supervised with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="neelrr/HW2-supervised")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("neelrr/HW2-supervised") model = AutoModelForCausalLM.from_pretrained("neelrr/HW2-supervised") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use neelrr/HW2-supervised with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "neelrr/HW2-supervised" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "neelrr/HW2-supervised", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/neelrr/HW2-supervised
- SGLang
How to use neelrr/HW2-supervised 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 "neelrr/HW2-supervised" \ --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": "neelrr/HW2-supervised", "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 "neelrr/HW2-supervised" \ --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": "neelrr/HW2-supervised", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use neelrr/HW2-supervised with Docker Model Runner:
docker model run hf.co/neelrr/HW2-supervised
- Xet hash:
- 8b0a879e1cdd98d973708c2d9a2f9e99d1648f1488548d8452a2b02c4b9f4787
- Size of remote file:
- 2.47 GB
- SHA256:
- 9b0c13e717a806945c15593f06cc7d720e48dd7cd8ffa1c616211306966dc67f
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