Video-Text-to-Text
Transformers
Safetensors
English
videollama3_qwen2
text-generation
multi-modal
large-language-model
video-language-model
custom_code
Instructions to use DAMO-NLP-SG/VideoLLaMA3-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DAMO-NLP-SG/VideoLLaMA3-2B with Transformers:
# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-SG/VideoLLaMA3-2B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Error in modeling_videollama3.py
#4
by aj70 - opened
Hi, I found a bug in your code where a call to self._compress_visual_tokens() in prepare_inputs_labels_for_multimodal() is made with the wrong order of accepted inputs. The current order is (compression_mask, mm_features, input_ids, attention_mask, labels, position_ids) where the correct order should instead be (compression_mask, mm_features, input_ids, attention_mask, position_ids, labels).
This bug is causing the position IDs to be set as labels and, as a result, throwing off the training. Please fix it.