Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use greenw0lf/wav2vec2-large-xls-r-1b-frisian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use greenw0lf/wav2vec2-large-xls-r-1b-frisian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="greenw0lf/wav2vec2-large-xls-r-1b-frisian")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("greenw0lf/wav2vec2-large-xls-r-1b-frisian") model = AutoModelForCTC.from_pretrained("greenw0lf/wav2vec2-large-xls-r-1b-frisian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload Wav2Vec2ForCTC
Browse files- config.json +4 -4
- pytorch_model.bin +2 -2
config.json
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{
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"_name_or_path": "
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"activation_dropout": 0.0,
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"adapter_kernel_size": 3,
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"adapter_stride": 2,
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"layerdrop": 0.1,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.
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"model_type": "wav2vec2",
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"num_adapter_layers": 3,
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"num_attention_heads": 16,
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],
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_weighted_layer_sum": false,
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"vocab_size": 45,
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"xvector_output_dim": 512
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{
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"_name_or_path": "/scratch/s3944867/XLS-R/wav2vec2-large-xls-r-1b-frisian/checkpoint-7200",
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"activation_dropout": 0.0,
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"adapter_kernel_size": 3,
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"adapter_stride": 2,
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"layerdrop": 0.1,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.3,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.3,
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"model_type": "wav2vec2",
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"num_adapter_layers": 3,
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"num_attention_heads": 16,
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1
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],
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"torch_dtype": "float32",
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"transformers_version": "4.28.1",
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"use_weighted_layer_sum": false,
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"vocab_size": 45,
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"xvector_output_dim": 512
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pytorch_model.bin
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size
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version https://git-lfs.github.com/spec/v1
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size 3850489709
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