Automatic Speech Recognition
Transformers
Safetensors
joint_aed_ctc_speech-encoder-decoder
custom_code
Instructions to use BUT-FIT/ED-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/ED-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BUT-FIT/ED-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("BUT-FIT/ED-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token_id": 0, | |
| "ctc_margin": 0, | |
| "ctc_weight": 0.3, | |
| "decoder_start_token_id": 0, | |
| "eos_token_id": 1, | |
| "max_length": 512, | |
| "num_beams": 5, | |
| "pad_token_id": 3, | |
| "transformers_version": "4.39.3" | |
| } | |