Instructions to use lfhe/FLock-Arena-Task-15-Carbonia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lfhe/FLock-Arena-Task-15-Carbonia with PEFT:
Task type is invalid.
- Transformers
How to use lfhe/FLock-Arena-Task-15-Carbonia with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lfhe/FLock-Arena-Task-15-Carbonia")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lfhe/FLock-Arena-Task-15-Carbonia", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use lfhe/FLock-Arena-Task-15-Carbonia with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lfhe/FLock-Arena-Task-15-Carbonia" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lfhe/FLock-Arena-Task-15-Carbonia", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lfhe/FLock-Arena-Task-15-Carbonia
- SGLang
How to use lfhe/FLock-Arena-Task-15-Carbonia 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 "lfhe/FLock-Arena-Task-15-Carbonia" \ --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": "lfhe/FLock-Arena-Task-15-Carbonia", "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 "lfhe/FLock-Arena-Task-15-Carbonia" \ --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": "lfhe/FLock-Arena-Task-15-Carbonia", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lfhe/FLock-Arena-Task-15-Carbonia with Docker Model Runner:
docker model run hf.co/lfhe/FLock-Arena-Task-15-Carbonia
- Xet hash:
- 31442ec15fdb96e7101d07dd916118dfcf08ea99cb0a0f6fffed856c7dc5f748
- Size of remote file:
- 3.62 MB
- SHA256:
- 2923f15e986925cfb5e017bc9acbe2e24add5218d2b44558e1283fe76bb6df04
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