Instructions to use pius-code/asha_twi_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pius-code/asha_twi_adapter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pius-code/asha_twi_adapter")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("pius-code/asha_twi_adapter") model = AutoModelForCTC.from_pretrained("pius-code/asha_twi_adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 50
Browse files- config.json +2 -2
- model.safetensors +2 -2
- preprocessor_config.json +1 -1
config.json
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"num_hidden_layers": 48,
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"num_negatives": 100,
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"output_hidden_size": 1280,
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"pad_token_id":
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"proj_codevector_dim": 1024,
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"tdnn_dilation": [
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1,
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"transformers_version": "5.13.0.dev0",
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"use_cache": false,
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"use_weighted_layer_sum": false,
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"vocab_size":
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"xvector_output_dim": 512
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}
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"num_hidden_layers": 48,
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"num_negatives": 100,
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"output_hidden_size": 1280,
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"pad_token_id": 41,
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"proj_codevector_dim": 1024,
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"tdnn_dilation": [
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1,
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"transformers_version": "5.13.0.dev0",
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"use_cache": false,
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"use_weighted_layer_sum": false,
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"vocab_size": 44,
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"xvector_output_dim": 512
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:d0e86c5322d957189aabf2eb0ef3212ecf7dc7b86f64d8eda63f3aefbca833d6
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size 3858957480
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preprocessor_config.json
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0,
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0.0,
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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