Automatic Speech Recognition
Transformers
Safetensors
seamless_m4t_v2
feature-extraction
audio-to-audio
text-to-speech
seamless_communication
Instructions to use osanseviero/seamless-copy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osanseviero/seamless-copy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="osanseviero/seamless-copy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("osanseviero/seamless-copy") model = AutoModel.from_pretrained("osanseviero/seamless-copy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from osanseviero/seamless-copy: direct link, hf CLI and curl.
- Browser
- Download file 5.17 MB
-
https://huggingface.co/osanseviero/seamless-copy/resolve/main/tokenizer.model
- Command line
-
hf download hf://osanseviero/seamless-copy/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/osanseviero/seamless-copy/resolve/main/tokenizer.model
5.17 MB
- Xet hash:
- 6b69da23df738e9760e0a97502ff053293b9affcb172e71abb9c3532ab1814a0
- Size of remote file:
- 5.17 MB
- SHA256:
- 026a76827537db9f1348e4d5aaa127bb10a2f2ff633243f3a52d16be82d73f9d
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