Automatic Speech Recognition
Transformers
NeMo
Safetensors
PyTorch
French
parakeet_rnnt
feature-extraction
speech
audio
Transducer
FastConformer
CTC
Transformer
NeMo
Eval Results (legacy)
Instructions to use linagora/linto_stt_fr_fastconformer_pc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linagora/linto_stt_fr_fastconformer_pc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="linagora/linto_stt_fr_fastconformer_pc")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("linagora/linto_stt_fr_fastconformer_pc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from linagora/linto_stt_fr_fastconformer_pc: direct link, hf CLI and curl.
- Browser
- Download file 187 Bytes
-
https://huggingface.co/linagora/linto_stt_fr_fastconformer_pc/resolve/main/generation_config.json
- Command line
-
hf download hf://linagora/linto_stt_fr_fastconformer_pc/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/linagora/linto_stt_fr_fastconformer_pc/resolve/main/generation_config.json
187 Bytes
| { | |
| "_from_model_config": true, | |
| "decoder_start_token_id": 1024, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "pad_token_id": 0, | |
| "transformers_version": "5.17.0" | |
| } | |