Instructions to use Vezel/Data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Vezel/Data with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Vezel/Data", dtype=torch.bfloat16, device_map="cuda") prompt = "My name is Wolfgang and I live in Berlin" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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Download README.md from Vezel/Data: direct link, hf CLI and curl.
- Browser
- Download file 290 Bytes
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https://huggingface.co/Vezel/Data/resolve/main/README.md
- Command line
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hf download hf://Vezel/Data/README.md
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curl -L -o README.md https://huggingface.co/Vezel/Data/resolve/main/README.md
290 Bytes
| license: mit | |
| datasets: | |
| - FreedomIntelligence/medical-o1-reasoning-SFT | |
| language: | |
| - en | |
| - ur | |
| - ar | |
| - hi | |
| metrics: | |
| - accuracy | |
| base_model: | |
| - deepseek-ai/Janus-Pro-7B | |
| new_version: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | |
| pipeline_tag: translation | |
| library_name: diffusers | |
| tags: | |
| - art | |
| - audio | |