Instructions to use Raiff1982/CodetteFineTuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Raiff1982/CodetteFineTuned with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("gpt2") model = PeftModel.from_pretrained(base_model, "Raiff1982/CodetteFineTuned") - Transformers
How to use Raiff1982/CodetteFineTuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Raiff1982/CodetteFineTuned")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Raiff1982/CodetteFineTuned", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Raiff1982/CodetteFineTuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Raiff1982/CodetteFineTuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Raiff1982/CodetteFineTuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Raiff1982/CodetteFineTuned
- SGLang
How to use Raiff1982/CodetteFineTuned 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 "Raiff1982/CodetteFineTuned" \ --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": "Raiff1982/CodetteFineTuned", "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 "Raiff1982/CodetteFineTuned" \ --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": "Raiff1982/CodetteFineTuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Raiff1982/CodetteFineTuned with Docker Model Runner:
docker model run hf.co/Raiff1982/CodetteFineTuned
Add 6 files
Browse files- adapter_model.safetensors +3 -0
- images/Codette_Quantum_Harmonic_Framework.png +3 -0
- optimizer.pt +3 -0
- scheduler.pt +3 -0
- training_args.bin +3 -0
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