Any-to-Any
Transformers
Safetensors
funaudiochat
text-generation
audio-visual
spoken-dialogue
talking-head
streaming
Instructions to use junseok520/JAVIS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junseok520/JAVIS with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("junseok520/JAVIS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from junseok520/JAVIS: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/junseok520/JAVIS/resolve/main/tokenizer.json
- Command line
-
hf download hf://junseok520/JAVIS/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/junseok520/JAVIS/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- dc0433a8bde65e957f8f169e6d7089bbfbf02c36e870e5a06b3edc343c8b411c
- Size of remote file:
- 11.4 MB
- SHA256:
- 7a7d58d42d29ac0776a3d5a6e6746fb0fe79dfe65fafa947f3dd76da528a02fe
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