Automatic Speech Recognition
Transformers
Safetensors
wav2vec2-bert
Generated from Trainer
Eval Results (legacy)
Instructions to use dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0") model = AutoModelForCTC.from_pretrained("dmusingu/w2v-bert-2.0-luganda-CV-train-validation-7.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Luganda ASR E-Branchformer
#1
by allandclive - opened
No, I am not. I'll take some time to review it. Btw thanks for pointing me to Wav2Vec-Bert 2. It produced significantly better results.