Instructions to use yvelos/Tes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yvelos/Tes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yvelos/Tes")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("yvelos/Tes") model = AutoModelForCausalLM.from_pretrained("yvelos/Tes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yvelos/Tes with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yvelos/Tes" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yvelos/Tes", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yvelos/Tes
- SGLang
How to use yvelos/Tes 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 "yvelos/Tes" \ --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": "yvelos/Tes", "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 "yvelos/Tes" \ --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": "yvelos/Tes", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yvelos/Tes with Docker Model Runner:
docker model run hf.co/yvelos/Tes
Download adapter_model.bin from yvelos/Tes: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/yvelos/Tes/resolve/main/adapter_model.bin
- Command line
-
hf download hf://yvelos/Tes/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/yvelos/Tes/resolve/main/adapter_model.bin
134 MB
- Xet hash:
- d31baabbf26ce38653e719f5a06f5c8b386436b0585b0d75a5eec534ee5b4b78
- Size of remote file:
- 134 MB
- SHA256:
- f4ae0162db1a854eecca239f628b9183dfb918d56602aca778c5febfa6abb81e
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