Instructions to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b787fb1d332ef21437ca4bc2f15194f2bc6e9e9ca106567ae3726c9069cfdd3d
- Size of remote file:
- 15.5 kB
- SHA256:
- 9eef17b9aba8e7fad56f89a2cd30d801422578764558582d0e5e74e392322bd9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.