Instructions to use eliem/Qwen2.5-VL-7B-radiology with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eliem/Qwen2.5-VL-7B-radiology with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="eliem/Qwen2.5-VL-7B-radiology")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("eliem/Qwen2.5-VL-7B-radiology") model = AutoModel.from_pretrained("eliem/Qwen2.5-VL-7B-radiology", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded finetuned model
- Developed by: eliem
- License: apache-2.0
- Finetuned from model : unsloth/Qwen2.5-VL-7B-Instruct-unsloth-bnb-4bit
This qwen2_5_vl model was trained 2x faster with Unsloth and Huggingface's TRL library.
- Downloads last month
- 8
Model tree for eliem/Qwen2.5-VL-7B-radiology
Base model
Qwen/Qwen2.5-VL-7B-Instruct