Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Russian
gigaam-ctc
asr
gigaam
stt
ctc
audio
speech
custom_code
Instructions to use waveletdeboshir/gigaam-ctc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use waveletdeboshir/gigaam-ctc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="waveletdeboshir/gigaam-ctc", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("waveletdeboshir/gigaam-ctc", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "added_tokens_decoder": { | |
| "33": { | |
| "content": "[BLANK]", | |
| "lstrip": true, | |
| "normalized": false, | |
| "rstrip": true, | |
| "single_word": false, | |
| "special": false | |
| } | |
| }, | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "do_lower_case": false, | |
| "eos_token": null, | |
| "model_max_length": 1000, | |
| "pad_token": "[BLANK]", | |
| "replace_word_delimiter_char": " ", | |
| "target_lang": null, | |
| "tokenizer_class": "GigaAMCTCTokenizer", | |
| "unk_token": "[BLANK]", | |
| "word_delimiter_token": " ", | |
| "auto_map": { | |
| "AutoTokenizer": ["gigaam_transformers.GigaAMCTCTokenizer", null] | |
| } | |
| } | |