Automatic Speech Recognition
Transformers
Oriya
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use varunril/odia_transcript_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varunril/odia_transcript_generation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="varunril/odia_transcript_generation")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("varunril/odia_transcript_generation") model = AutoModelForCTC.from_pretrained("varunril/odia_transcript_generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from varunril/odia_transcript_generation: direct link, hf CLI and curl.
- Browser
- Download file 353 Bytes
-
https://huggingface.co/varunril/odia_transcript_generation/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://varunril/odia_transcript_generation/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/varunril/odia_transcript_generation/resolve/main/tokenizer_config.json
353 Bytes
| {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "special_tokens_map_file": "/content/drive/MyDrive/ASR_models/wav2vec2-large-xlsr-odia/special_tokens_map.json", "tokenizer_file": null, "name_or_path": "/content/drive/MyDrive/ASR_models/wav2vec2-large-xlsr-odia"} |