Instructions to use JoydeepC/trueGL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoydeepC/trueGL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="JoydeepC/trueGL")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("JoydeepC/trueGL") model = AutoModelForCausalLM.from_pretrained("JoydeepC/trueGL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use JoydeepC/trueGL with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "JoydeepC/trueGL" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JoydeepC/trueGL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/JoydeepC/trueGL
- SGLang
How to use JoydeepC/trueGL 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 "JoydeepC/trueGL" \ --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": "JoydeepC/trueGL", "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 "JoydeepC/trueGL" \ --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": "JoydeepC/trueGL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use JoydeepC/trueGL with Docker Model Runner:
docker model run hf.co/JoydeepC/trueGL
File size: 688 Bytes
ca4eb5b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | import os
from huggingface_hub import HfApi
# Initialize the Hugging Face API client
api = HfApi(token=os.getenv("HF_TOKEN"))
# Create the repository if it doesn't exist
try:
api.create_repo(repo_id="JoydeepC/trueGL", repo_type="model", private=False)
print("Repository created successfully!")
except Exception as e:
print(f"Repository already exists or error: {e}")
# Upload the model folder to the Hugging Face Hub
api.upload_folder(
folder_path="E:\model_us",
repo_id="JoydeepC/trueGL",
repo_type="model",
commit_message="Upload fine-tuned trueGL model",
create_pr=False
)
print("Model uploaded successfully to JoydeepC/trueGL!") |