Automatic Speech Recognition
Transformers
PyTorch
Hindi
wav2vec2
hf-asr-leaderboard
model_for_talk
mozilla-foundation/common_voice_7_0
robust-speech-event
Eval Results (legacy)
Instructions to use Harveenchadha/hindi_base_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harveenchadha/hindi_base_wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Harveenchadha/hindi_base_wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Harveenchadha/hindi_base_wav2vec2") model = AutoModelForCTC.from_pretrained("Harveenchadha/hindi_base_wav2vec2") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
language:
- hi
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- hi
- model_for_talk
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- Harveenchadha/indic-voice
model-index:
- name: Hindi Large
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice
type: common_voice
args: hi
metrics:
- name: Test WER
type: wer
value: 22.62
- name: Test CER
type: cer
value: 7.42
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice-7.0
type: mozilla-foundation/common_voice_7_0
args: hi
metrics:
- name: Test WER
type: wer
value: 19.47
- name: Test CER
type: cer
value: 8.05
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice-8.0
type: mozilla-foundation/common_voice_8_0
args: hi
metrics:
- name: Test WER
type: wer
value: 20.87
- name: Test CER
type: cer
value: 9.47