Audio Classification
Transformers
ONNX
NeMo
Safetensors
anuvani_lid
audio
speech
language-identification
spoken-language-id
lid
indic
conformer
custom_code
Instructions to use CIIL/Anuvani-LID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIIL/Anuvani-LID with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="CIIL/Anuvani-LID", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForAudioClassification model = AutoModelForAudioClassification.from_pretrained("CIIL/Anuvani-LID", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from CIIL/Anuvani-LID: direct link, hf CLI and curl.
- Browser
- Download file 1.67 kB
-
https://huggingface.co/CIIL/Anuvani-LID/resolve/main/config.json
- Command line
-
hf download hf://CIIL/Anuvani-LID/config.json
-
curl -L -o config.json https://huggingface.co/CIIL/Anuvani-LID/resolve/main/config.json
1.67 kB
| { | |
| "_attn_implementation_autoset": true, | |
| "architectures": [ | |
| "AnuvaniLidForAudioClassification" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_anuvani_lid.AnuvaniLidConfig", | |
| "AutoModelForAudioClassification": "modeling_anuvani_lid.AnuvaniLidForAudioClassification" | |
| }, | |
| "conv_kernel_size": 31, | |
| "d_ff": 2048, | |
| "d_model": 512, | |
| "hop_length": 160, | |
| "id2label": { | |
| "0": "assamese", | |
| "1": "bengali", | |
| "2": "bodo", | |
| "3": "dogri", | |
| "4": "english", | |
| "5": "gujarati", | |
| "6": "hindi", | |
| "7": "kannada", | |
| "8": "kashmiri", | |
| "9": "konkani", | |
| "10": "maithili", | |
| "11": "malayalam", | |
| "12": "manipuri", | |
| "13": "marathi", | |
| "14": "nepali", | |
| "15": "odia", | |
| "16": "punjabi", | |
| "17": "sanskrit", | |
| "18": "santali", | |
| "19": "sindhi", | |
| "20": "tamil", | |
| "21": "telugu", | |
| "22": "urdu" | |
| }, | |
| "label2id": { | |
| "assamese": 0, | |
| "bengali": 1, | |
| "bodo": 2, | |
| "dogri": 3, | |
| "english": 4, | |
| "gujarati": 5, | |
| "hindi": 6, | |
| "kannada": 7, | |
| "kashmiri": 8, | |
| "konkani": 9, | |
| "maithili": 10, | |
| "malayalam": 11, | |
| "manipuri": 12, | |
| "marathi": 13, | |
| "nepali": 14, | |
| "odia": 15, | |
| "punjabi": 16, | |
| "sanskrit": 17, | |
| "santali": 18, | |
| "sindhi": 19, | |
| "tamil": 20, | |
| "telugu": 21, | |
| "urdu": 22 | |
| }, | |
| "layer_agg_per_channel_scale": false, | |
| "layer_agg_pre_layernorm": false, | |
| "layer_aggregation": true, | |
| "model_type": "anuvani_lid", | |
| "n_fft": 512, | |
| "n_heads": 8, | |
| "n_layers": 17, | |
| "n_mels": 80, | |
| "pad_to": 16, | |
| "pos_emb_max_len": 5000, | |
| "preemph": 0.97, | |
| "sample_rate": 16000, | |
| "subsampling_conv_channels": 512, | |
| "transformers_version": "4.46.3", | |
| "win_length": 400 | |
| } |