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/refs%2Fpr%2F65/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText@refs/pr/65/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-SeamlessM4Tv2ForTextToText/resolve/refs%2Fpr%2F65/model.safetensors
15.5 kB
- Xet hash:
- 72e4fa85bfa24f47319e8e3943ac8777098fc4358b81ee1202e74373b6d67432
- Size of remote file:
- 15.5 kB
- SHA256:
- f0b347b832e89e8f8ca035bff8d9c77213f6d9a64281fd8596c9b91e7b516ed0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.