Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
Generated from Trainer
Instructions to use sanchit-gandhi/wav2vec2-2-bart-debug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanchit-gandhi/wav2vec2-2-bart-debug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sanchit-gandhi/wav2vec2-2-bart-debug")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("sanchit-gandhi/wav2vec2-2-bart-debug") model = AutoModelForSpeechSeq2Seq.from_pretrained("sanchit-gandhi/wav2vec2-2-bart-debug", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sanchit-gandhi/wav2vec2-2-bart-debug: direct link, hf CLI and curl.
- Browser
- Download file 2.35 GB
-
https://huggingface.co/sanchit-gandhi/wav2vec2-2-bart-debug/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sanchit-gandhi/wav2vec2-2-bart-debug/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sanchit-gandhi/wav2vec2-2-bart-debug/resolve/main/pytorch_model.bin
2.35 GB
- Xet hash:
- a583c030cded471a7a0c6784b7525971499aaaa79fc466fd14f8e53d74b65199
- Size of remote file:
- 2.35 GB
- SHA256:
- 66563613eae4596f615d770133a0ca3abee4e356c20823933fbeb7bbd91b8ee2
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