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
-
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
metadata
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