Video-Text-to-Text
Transformers
Safetensors
llava_next_video
image-text-to-text
llava
video
sign-language
multimodal
Instructions to use Remostart/sign-language with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Remostart/sign-language with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Remostart/sign-language") model = AutoModelForMultimodalLM.from_pretrained("Remostart/sign-language", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| base_model: llava-hf/LLaVA-NeXT-Video-7B-hf | |
| pipeline_tag: video-text-to-text | |
| library_name: transformers | |
| tags: | |
| - llava | |
| - video | |
| - sign-language | |
| - multimodal | |
| # Sign Language Translation Model (LLaVA Fine-tuned) | |
| This is a fine-tuned version of [LLaVA-NeXT-Video-7B](https://huggingface.co/llava-hf/LLaVA-NeXT-Video-7B-hf) for sign language translation. | |
| ## Usage | |
| ```python | |
| from transformers import LlavaNextVideoForConditionalGeneration, AutoProcessor | |
| import torch | |
| model = LlavaNextVideoForConditionalGeneration.from_pretrained("Remostart/sign-language") | |
| processor = AutoProcessor.from_pretrained("Remostart/sign-language") |