Instructions to use BUT-FIT/DiCoW_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/DiCoW_v2 with Transformers:
# Load model directly from transformers import AutoProcessor, WhisperForConditionalGenerationWithCTC processor = AutoProcessor.from_pretrained("BUT-FIT/DiCoW_v2") model = WhisperForConditionalGenerationWithCTC.from_pretrained("BUT-FIT/DiCoW_v2") - Notebooks
- Google Colab
- Kaggle
Update generation_config.json
Browse files- generation_config.json +0 -1
generation_config.json
CHANGED
|
@@ -140,7 +140,6 @@
|
|
| 140 |
"<|yue|>": 50358,
|
| 141 |
"<|zh|>": 50260
|
| 142 |
},
|
| 143 |
-
"language": "english",
|
| 144 |
"max_initial_timestamp_index": 50,
|
| 145 |
"max_length": 448,
|
| 146 |
"mt_num_speakers": 1,
|
|
|
|
| 140 |
"<|yue|>": 50358,
|
| 141 |
"<|zh|>": 50260
|
| 142 |
},
|
|
|
|
| 143 |
"max_initial_timestamp_index": 50,
|
| 144 |
"max_length": 448,
|
| 145 |
"mt_num_speakers": 1,
|