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
RL — RAFT on Recipe I (Reward rAnked FineTuning). Tag F1 28%, Tag Recall 50%, -5pp hallucination vs SFT. Pair with base for ASR; see serve_modal.py Mode B hybrid. https://github.com/YongkangZOU/evoxtral-realtime
acfd33d verified - Xet hash:
- dd2cad65ec6d3ae5a0d05e8391994f0bee42353575eaae775dd76e6b70673948
- Size of remote file:
- 14.9 MB
- SHA256:
- 8434af1d39eba99f0ef46cf1450bf1a63fa941a26933a1ef5dbbf4adf0d00e44
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