Video-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
text-generation-inference
Instructions to use QiWang98/VideoRFT-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QiWang98/VideoRFT-SFT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("QiWang98/VideoRFT-SFT") model = AutoModelForMultimodalLM.from_pretrained("QiWang98/VideoRFT-SFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from QiWang98/VideoRFT-SFT: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/QiWang98/VideoRFT-SFT/resolve/main/tokenizer.json
- Command line
-
hf download hf://QiWang98/VideoRFT-SFT/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/QiWang98/VideoRFT-SFT/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- f8d5dc3430f301e3334c34268c690e5b8dfdc152b46f525db04e968ddb6379ba
- Size of remote file:
- 11.4 MB
- SHA256:
- ba0c439f7be467bf47d12a7e6f9adc6116201056fc60c67f431c679b7c16afc8
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