Instructions to use hf-internal-testing/tiny-random-SeamlessM4Tv2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SeamlessM4Tv2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SeamlessM4Tv2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SeamlessM4Tv2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec01d5e1ebc3fec149881a84aa5bdc2bca39b0bc64e44bf7c2546d0c1a6e24c5
- Size of remote file:
- 338 kB
- SHA256:
- 217a86bd0793c4698c29bd3fe488115a513f20b04a5c76d9e75ebeaf3e0973b8
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