Video-Text-to-Text
Transformers
Safetensors
English
llava
text-generation
multimodal
vision-language
video understanding
spatial reasoning
visuospatial cognition
qwen
llava-video
Instructions to use nkkbr/ViCA-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkkbr/ViCA-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("nkkbr/ViCA-base") model = AutoModelForCausalLM.from_pretrained("nkkbr/ViCA-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from nkkbr/ViCA-base: direct link, hf CLI and curl.
- Browser
- Download file 367 Bytes
-
https://huggingface.co/nkkbr/ViCA-base/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://nkkbr/ViCA-base/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/nkkbr/ViCA-base/resolve/main/special_tokens_map.json
367 Bytes
| { | |
| "additional_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>" | |
| ], | |
| "eos_token": { | |
| "content": "<|im_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |