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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license: mit
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---
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license: mit
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datasets:
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- FreedomIntelligence/medical-o1-reasoning-SFT
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language:
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- en
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- ur
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- ar
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- hi
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metrics:
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- accuracy
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base_model:
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- deepseek-ai/Janus-Pro-7B
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new_version: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
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pipeline_tag: translation
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library_name: diffusers
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tags:
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- art
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- audio
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