Instructions to use yvelos/Test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yvelos/Test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yvelos/Test1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("yvelos/Test1") model = AutoModelForCausalLM.from_pretrained("yvelos/Test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yvelos/Test1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yvelos/Test1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yvelos/Test1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yvelos/Test1
- SGLang
How to use yvelos/Test1 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/Test1" \ --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/Test1", "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/Test1" \ --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/Test1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yvelos/Test1 with Docker Model Runner:
docker model run hf.co/yvelos/Test1
Download pytorch_model.bin from yvelos/Test1: direct link, hf CLI and curl.
- Browser
- Download file 3.91 GB
-
https://huggingface.co/yvelos/Test1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yvelos/Test1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yvelos/Test1/resolve/main/pytorch_model.bin
3.91 GB
- Xet hash:
- 1d672d002602c2473ba2e07fd1249659b1db5468c64a438d5232bf4141592d51
- Size of remote file:
- 3.91 GB
- SHA256:
- 16bef664ee1ceb77f65dad714d99db3bdbe919fda5881bcb64b7960790d3a804
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.