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:
- 8361fdc0e3629cc7e4537c88fe11dd4a6a8810f936c8ace4b7f6661cbc44e538
- Size of remote file:
- 15.5 kB
- SHA256:
- 525a04ba024200e98bf528b014b1441ad080a79f34884d019239d89a2a0f0841
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.