Automatic Speech Recognition
PEFT
Safetensors
audio
lora
voxtral
voxtral-realtime
affect-tagging
expressive-tags
half-duplex
elevenlabs-tags
raft
rejection-sampling
rlhf
Instructions to use YongkangZOU/evoxtral-realtime-rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use YongkangZOU/evoxtral-realtime-rl with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Voxtral-Mini-4B-Realtime-2602") model = PeftModel.from_pretrained(base_model, "YongkangZOU/evoxtral-realtime-rl") - Notebooks
- Google Colab
- Kaggle
File size: 384 Bytes
acfd33d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"feature_extractor": {
"feature_extractor_type": "VoxtralRealtimeFeatureExtractor",
"feature_size": 128,
"global_log_mel_max": 1.5,
"hop_length": 160,
"n_fft": 400,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000,
"win_length": 400
},
"processor_class": "VoxtralRealtimeProcessor"
}
|