Token Classification
Transformers
Safetensors
English
bert
transcript-cleanup
experimental
keep-delete
Instructions to use arach/transcript-cleanup-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arach/transcript-cleanup-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arach/transcript-cleanup-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arach/transcript-cleanup-tiny") model = AutoModelForTokenClassification.from_pretrained("arach/transcript-cleanup-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 521 Bytes
8dc2230 | 1 2 3 4 5 6 7 8 9 | Transcript cleanup tiny, experimental fine-tune by Arach, 2026.
Derived from Google BERT-Tiny (google/bert_uncased_L-2_H-128_A-2),
revision 30b0a37ccaaa32f332884b96992754e246e48c5f, Apache License 2.0.
Modifications: a new KEEP/DELETE token-classification head and full-model
fine-tuning on assistant-authored synthetic cleanup examples.
The tokenizer is redistributed unchanged.
Base model: https://huggingface.co/google/bert_uncased_L-2_H-128_A-2
Recipe code has a separate MIT license; Parakeet weights use CC-BY-4.0.
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