Audio Classification
Transformers
PyTorch
Safetensors
Russian
unispeech-sat
emotion-recognition
speech-emotion-recognition
audio
speech
russian
Eval Results (legacy)
Instructions to use Aniemore/unispeech-sat-emotion-russian-resd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aniemore/unispeech-sat-emotion-russian-resd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Aniemore/unispeech-sat-emotion-russian-resd")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Aniemore/unispeech-sat-emotion-russian-resd") model = AutoModelForAudioClassification.from_pretrained("Aniemore/unispeech-sat-emotion-russian-resd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Aniemore/unispeech-sat-emotion-russian-resd: direct link, hf CLI and curl.
- Browser
- Download file 96 Bytes
-
https://huggingface.co/Aniemore/unispeech-sat-emotion-russian-resd/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Aniemore/unispeech-sat-emotion-russian-resd/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Aniemore/unispeech-sat-emotion-russian-resd/resolve/main/special_tokens_map.json
96 Bytes
| { | |
| "bos_token": "<s>", | |
| "eos_token": "</s>", | |
| "pad_token": "<pad>", | |
| "unk_token": "<unk>" | |
| } | |