Feature Extraction
Transformers
Safetensors
qwen2_5_vl
image-text-to-text
embedding
multimodal
vision-language
mmeb
mveb
Instructions to use HugC/VisME-Qwen25VL-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HugC/VisME-Qwen25VL-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="HugC/VisME-Qwen25VL-3B")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("HugC/VisME-Qwen25VL-3B") model = AutoModelForMultimodalLM.from_pretrained("HugC/VisME-Qwen25VL-3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token_id": 151643, | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "pad_token_id": 151643, | |
| "repetition_penalty": 1.05, | |
| "temperature": 1e-06, | |
| "transformers_version": "4.57.3" | |
| } | |