Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use TheRains/yt-special-batch8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheRains/yt-special-batch8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheRains/yt-special-batch8")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TheRains/yt-special-batch8") model = AutoModelForSpeechSeq2Seq.from_pretrained("TheRains/yt-special-batch8") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_bos_token": false, | |
| "add_prefix_space": false, | |
| "bos_token": { | |
| "__type": "AddedToken", | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": { | |
| "__type": "AddedToken", | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "errors": "replace", | |
| "model_max_length": 1024, | |
| "pad_token": null, | |
| "processor_class": "WhisperProcessor", | |
| "return_attention_mask": false, | |
| "tokenizer_class": "WhisperTokenizer", | |
| "unk_token": { | |
| "__type": "AddedToken", | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |