Automatic Speech Recognition
Transformers
Safetensors
voxtral
feature-extraction
speech
speech-language-model
question-answering
spoken-question-answering
speaker-diarization
meeting-transcription
Dixtral
Voxtral
DiCoW
BUT-FIT
custom_code
Instructions to use BUT-FIT/Dixtral_QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/Dixtral_QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BUT-FIT/Dixtral_QA", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("BUT-FIT/Dixtral_QA", trust_remote_code=True) model = AutoModel.from_pretrained("BUT-FIT/Dixtral_QA", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "pad_token_id": 11, | |
| "transformers_version": "4.55.0" | |
| } | |