Text Generation
Transformers
TensorBoard
Safetensors
English
gpt2
Generated from Trainer
text-generation-inference
Instructions to use Wonder-Griffin/squadtrainTraXL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wonder-Griffin/squadtrainTraXL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Wonder-Griffin/squadtrainTraXL")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Wonder-Griffin/squadtrainTraXL") model = AutoModelForCausalLM.from_pretrained("Wonder-Griffin/squadtrainTraXL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Wonder-Griffin/squadtrainTraXL with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Wonder-Griffin/squadtrainTraXL" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Wonder-Griffin/squadtrainTraXL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Wonder-Griffin/squadtrainTraXL
- SGLang
How to use Wonder-Griffin/squadtrainTraXL 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 "Wonder-Griffin/squadtrainTraXL" \ --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": "Wonder-Griffin/squadtrainTraXL", "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 "Wonder-Griffin/squadtrainTraXL" \ --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": "Wonder-Griffin/squadtrainTraXL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Wonder-Griffin/squadtrainTraXL with Docker Model Runner:
docker model run hf.co/Wonder-Griffin/squadtrainTraXL
Download modules.json from Wonder-Griffin/squadtrainTraXL: direct link, hf CLI and curl.
- Browser
- Download file 229 Bytes
-
https://huggingface.co/Wonder-Griffin/squadtrainTraXL/resolve/main/modules.json
- Command line
-
hf download hf://Wonder-Griffin/squadtrainTraXL/modules.json
-
curl -L -o modules.json https://huggingface.co/Wonder-Griffin/squadtrainTraXL/resolve/main/modules.json
229 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| } | |
| ] |