Instructions to use vtlustos/whisper-large-v2_lora_int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vtlustos/whisper-large-v2_lora_int8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vtlustos/whisper-large-v2_lora_int8")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vtlustos/whisper-large-v2_lora_int8") model = AutoModelForSpeechSeq2Seq.from_pretrained("vtlustos/whisper-large-v2_lora_int8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model_name_or_path": "openai/whisper-large-v2", | |
| "bias": "none", | |
| "enable_lora": null, | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "lora_alpha": 16, | |
| "lora_dropout": 0.05, | |
| "merge_weights": false, | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 16, | |
| "target_modules": [ | |
| "q_proj", | |
| "v_proj" | |
| ], | |
| "task_type": null | |
| } |