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:
- 4df5c803d0257c8b00db19dafff0a530db41e7310ff2ed84fa36bbb142153578
- Size of remote file:
- 15.5 kB
- SHA256:
- 276cedb767982308f18df73d5f11d7de90b560d65a582e287a2293d2e5883f76
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.