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:
- 80ba7e18f6d3d31ed19f15797f99886a1796369f4880fb862cd145438be0a1d7
- Size of remote file:
- 15.5 kB
- SHA256:
- 6971be6ce70d242306d8230a4c40ac0abe002eed29cefd472fcc09c3afb6006c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.