Automatic Speech Recognition
Transformers
Safetensors
English
asr_model
asr
speech-recognition
speech-to-text
audio
speech-llm
word-timestamps
speaker-diarization
qwen
granite-speech
lora
custom_code
Eval Results (legacy)
Instructions to use mazesmazes/tiny-audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mazesmazes/tiny-audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mazesmazes/tiny-audio", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("mazesmazes/tiny-audio", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from mazesmazes/tiny-audio: direct link, hf CLI and curl.
- Browser
- Download file 231 Bytes
-
https://huggingface.co/mazesmazes/tiny-audio/resolve/main/generation_config.json
- Command line
-
hf download hf://mazesmazes/tiny-audio/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/mazesmazes/tiny-audio/resolve/main/generation_config.json
231 Bytes
| { | |
| "_from_model_config": true, | |
| "eos_token_id": [ | |
| 248046, | |
| 248046, | |
| 248044 | |
| ], | |
| "max_new_tokens": 256, | |
| "no_repeat_ngram_size": 12, | |
| "pad_token_id": 248044, | |
| "transformers_version": "5.17.0", | |
| "use_cache": true | |
| } | |