Instructions to use Duckq/NLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Duckq/NLP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Duckq/NLP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Duckq/NLP") model = AutoModelForSequenceClassification.from_pretrained("Duckq/NLP") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer from 1_scratch_deberta_v3.ipynb
Browse files- spm_bpe_tokenizer.model +3 -0
spm_bpe_tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:c50e7746dfefe9afc7414af06139637c3a6eb411c06ccf3ade5ed0b60c0e99f7
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size 757656
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