Visual Question Answering
Transformers
Safetensors
English
videollama3_qwen2
text-generation
multi-modal
large-language-model
video-language-model
custom_code
Instructions to use DAMO-NLP-SG/VideoLLaMA3-7B-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DAMO-NLP-SG/VideoLLaMA3-7B-Image with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="DAMO-NLP-SG/VideoLLaMA3-7B-Image", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DAMO-NLP-SG/VideoLLaMA3-7B-Image", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add any-to-any pipeline tag, paper link
#1
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -15,18 +15,17 @@ language:
|
|
| 15 |
- en
|
| 16 |
metrics:
|
| 17 |
- accuracy
|
| 18 |
-
pipeline_tag:
|
| 19 |
base_model:
|
| 20 |
- Qwen/Qwen2.5-7B-Instruct
|
| 21 |
---
|
| 22 |
|
| 23 |
-
|
| 24 |
<p align="center">
|
| 25 |
<img src="https://cdn-uploads.huggingface.co/production/uploads/626938b16f8f86ad21deb989/tt5KYnAUmQlHtfB1-Zisl.png" width="150" style="margin-bottom: 0.2;"/>
|
| 26 |
<p>
|
| 27 |
|
| 28 |
|
| 29 |
-
<h3 align="center"><a href="https://
|
| 30 |
|
| 31 |
<h5 align="center">
|
| 32 |
|
|
|
|
| 15 |
- en
|
| 16 |
metrics:
|
| 17 |
- accuracy
|
| 18 |
+
pipeline_tag: any-to-any
|
| 19 |
base_model:
|
| 20 |
- Qwen/Qwen2.5-7B-Instruct
|
| 21 |
---
|
| 22 |
|
|
|
|
| 23 |
<p align="center">
|
| 24 |
<img src="https://cdn-uploads.huggingface.co/production/uploads/626938b16f8f86ad21deb989/tt5KYnAUmQlHtfB1-Zisl.png" width="150" style="margin-bottom: 0.2;"/>
|
| 25 |
<p>
|
| 26 |
|
| 27 |
|
| 28 |
+
<h3 align="center"><a href="https://huggingface.co/papers/2501.13106">VideoLLaMA 3: Frontier Multimodal Foundation Models for Video Understanding</a></h3>
|
| 29 |
|
| 30 |
<h5 align="center">
|
| 31 |
|