Instructions to use Tristo/ASDGASDFHASH with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tristo/ASDGASDFHASH with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Tristo/ASDGASDFHASH")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Tristo/ASDGASDFHASH") model = AutoModelForCausalLM.from_pretrained("Tristo/ASDGASDFHASH", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Tristo/ASDGASDFHASH with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Tristo/ASDGASDFHASH" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Tristo/ASDGASDFHASH", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Tristo/ASDGASDFHASH
- SGLang
How to use Tristo/ASDGASDFHASH 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 "Tristo/ASDGASDFHASH" \ --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": "Tristo/ASDGASDFHASH", "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 "Tristo/ASDGASDFHASH" \ --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": "Tristo/ASDGASDFHASH", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Tristo/ASDGASDFHASH with Docker Model Runner:
docker model run hf.co/Tristo/ASDGASDFHASH
- Xet hash:
- 8eb1c99f41f16f1810248837857784fea379c2c05be83ffddcce24f9b3332e6b
- Size of remote file:
- 510 MB
- SHA256:
- 3c0b4cd420ebc4aa1285bac63b8fb2acfbfba458b5da6d959b052888cb154b74
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