Transformers
Safetensors
English
pyannet
speaker-diarization
speaker-segmentation
Generated from Trainer
Instructions to use JSWOOK/pyannote_2_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JSWOOK/pyannote_2_finetuning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JSWOOK/pyannote_2_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from JSWOOK/pyannote_2_finetuning: direct link, hf CLI and curl.
- Browser
- Download file 350 Bytes
-
https://huggingface.co/JSWOOK/pyannote_2_finetuning/resolve/main/config.json
- Command line
-
hf download hf://JSWOOK/pyannote_2_finetuning/config.json
-
curl -L -o config.json https://huggingface.co/JSWOOK/pyannote_2_finetuning/resolve/main/config.json
350 Bytes
| { | |
| "architectures": [ | |
| "SegmentationModel" | |
| ], | |
| "chunk_duration": 10.0, | |
| "max_speakers_per_chunk": 3, | |
| "max_speakers_per_frame": 2, | |
| "min_duration": null, | |
| "model_type": "pyannet", | |
| "sample_rate": 16000, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.44.2", | |
| "warm_up": [ | |
| 0.0, | |
| 0.0 | |
| ], | |
| "weigh_by_cardinality": false | |
| } | |