Token Classification
Transformers
Safetensors
English
bert
prompt-compression
tiny-model
synthetic-data
Instructions to use aayushbist/saccade-tiny-100k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aayushbist/saccade-tiny-100k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aayushbist/saccade-tiny-100k")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aayushbist/saccade-tiny-100k") model = AutoModelForTokenClassification.from_pretrained("aayushbist/saccade-tiny-100k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b53fb6cf6ed25f5d282847637809a8375ae4508b33d520361305e668a92dbcd3
- Size of remote file:
- 5.27 kB
- SHA256:
- bbd68166292a8825551a64cc87c7a80130c3cf94f51ecbeb1c366bb0be3e6ce6
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