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:
# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText: direct link, hf CLI and curl.
- Browser
- Download file 15.5 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText/resolve/main/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText/resolve/main/model.safetensors
15.5 kB
- Xet hash:
- 50e69f5c13fc7ad6edb8d9933a376ba9ce8f5c23b7a7e4d91edb5854cad7ce85
- Size of remote file:
- 15.5 kB
- SHA256:
- bc78247ac972368041b18957fbffec80627ea06c2d501b3e749842c3724433af
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.