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:
- d4173b6be0e022382f1b84afb8b7e7b04840af097d8255e224fc0456451a2490
- Size of remote file:
- 15.5 kB
- SHA256:
- 41fcbe7616a0d2c689ef7e943da063fc6faf8ec3f96699cbfc0f7a560fbac868
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.