Automatic Speech Recognition
Transformers
JAX
TensorBoard
ONNX
Safetensors
Transformers.js
English
whisper
audio
Instructions to use tensorlake/distil-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorlake/distil-large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tensorlake/distil-large-v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tensorlake/distil-large-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("tensorlake/distil-large-v3", device_map="auto") - Transformers.js
How to use tensorlake/distil-large-v3 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'tensorlake/distil-large-v3'); - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from tensorlake/distil-large-v3: direct link, hf CLI and curl.
- Browser
- Download file 3.03 GB
-
https://huggingface.co/tensorlake/distil-large-v3/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://tensorlake/distil-large-v3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/tensorlake/distil-large-v3/resolve/main/flax_model.msgpack
3.03 GB
- Xet hash:
- 273bbdd34502082d5831395287cd7f424b41ada61d98e28de3cfb1266feada04
- Size of remote file:
- 3.03 GB
- SHA256:
- 439f6f1118e19519c2cbcdb6eb9026faddc3a86f8b8f1fd6455bf20ad5aaae15
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.