Text Classification
Transformers
PyTorch
Arabic
bert
hate-speech
gender-based-violence
arabic
binary-classification
pilot
Eval Results (legacy)
text-embeddings-inference
Instructions to use thejosango/nuha-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thejosango/nuha-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thejosango/nuha-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thejosango/nuha-binary") model = AutoModelForSequenceClassification.from_pretrained("thejosango/nuha-binary") - Notebooks
- Google Colab
- Kaggle
binary-45
Browse files- config.toml +2 -2
- tokenizer.json +8 -1
- training_args.bin +1 -1
config.toml
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[experiment]
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name = "binary-
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type = "binary"
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[dataset]
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path = "thejosango/nuha-dataset"
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dataset_revision = "main"
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augment_ratio = 0.
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undersampling_strategy = true
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[experiment]
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name = "binary-45"
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type = "binary"
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[dataset]
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path = "thejosango/nuha-dataset"
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dataset_revision = "main"
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augment_ratio = 0.75
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undersampling_strategy = true
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tokenizer.json
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"strategy": "LongestFirst",
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"stride": 0
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},
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"padding":
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"added_tokens": [
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{
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"id": 0,
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"strategy": "LongestFirst",
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"stride": 0
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},
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"padding": {
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"strategy": "BatchLongest",
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"direction": "Right",
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"pad_to_multiple_of": null,
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"pad_id": 0,
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"pad_type_id": 0,
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"pad_token": "[PAD]"
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},
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"added_tokens": [
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{
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"id": 0,
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 4091
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version https://git-lfs.github.com/spec/v1
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oid sha256:c269eb8f06bac306a9bb5f4f9cba0945fa170243feac8c6c760ce63faaca016a
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size 4091
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