Automatic Speech Recognition
Transformers
Safetensors
Arabic
English
cohere_asr
arabic
code-switching
decoder-only-finetune
Instructions to use nsa01n/cohere-cs-decoder-top with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nsa01n/cohere-cs-decoder-top with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nsa01n/cohere-cs-decoder-top")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nsa01n/cohere-cs-decoder-top") model = AutoModelForSpeechSeq2Seq.from_pretrained("nsa01n/cohere-cs-decoder-top", device_map="auto") - Notebooks
- Google Colab
- Kaggle
decoder-only fine-tune (top)
Browse files- model.safetensors +1 -1
- train_meta.json +5 -5
- training_args.bin +1 -1
model.safetensors
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train_meta.json
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"train_examples": 2780,
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"val_examples": 454,
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"metrics": {
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second": 0.
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"total_flos": 2.618070162836816e+19,
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"train_loss": 0.
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"epoch": 2.0
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"freeze": {
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"optim": "adamw_bnb_8bit",
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"weight_decay": 0.01,
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"max_grad_norm": 1.0,
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"save_total_limit":
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}
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}
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"train_examples": 2780,
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"val_examples": 454,
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"metrics": {
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"train_runtime": 248.5116,
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"train_samples_per_second": 22.373,
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"train_steps_per_second": 0.7,
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"total_flos": 2.618070162836816e+19,
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"train_loss": 0.1957648105319889,
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"epoch": 2.0
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},
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"freeze": {
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"optim": "adamw_bnb_8bit",
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"weight_decay": 0.01,
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"max_grad_norm": 1.0,
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"save_total_limit": 1
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}
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}
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training_args.bin
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size 5393
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