Instructions to use hts98/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/model") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from hts98/model: direct link, hf CLI and curl.
- Browser
- Download file 3.06 GB
-
https://huggingface.co/hts98/model/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://hts98/model/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/hts98/model/resolve/main/flax_model.msgpack
3.06 GB
- Xet hash:
- e7d871b6d1ca458475dcd1a98f869f67011769928a31a858e30fd1c385155174
- Size of remote file:
- 3.06 GB
- SHA256:
- 7aac2fb628c8f7a78748c03d78d339e01ba3072c42086f65fe205e7eb21e8f32
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