Text Classification
PEFT
Safetensors
Arabic
French
darija
arabic
moroccan-arabic
arabizi
nlp
lora
bertouch
Instructions to use MedAdil/BERTal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MedAdil/BERTal with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("AbderrahmanSkiredj1/BERTouch") model = PeftModel.from_pretrained(base_model, "MedAdil/BERTal") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer_config.json with huggingface_hub
Browse files- tokenizer_config.json +30 -0
tokenizer_config.json
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{
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"backend": "tokenizers",
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": false,
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"is_local": false,
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"mask_token": "[MASK]",
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"max_len": 512,
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"max_length": 128,
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"model_max_length": 512,
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"never_split": [
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"[بريد]",
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"[مستخدم]",
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"[رابط]"
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],
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"pad_to_multiple_of": null,
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"pad_token": "[PAD]",
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"pad_token_type_id": 0,
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"padding_side": "right",
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"sep_token": "[SEP]",
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"stride": 0,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "[UNK]",
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"use_fast": true
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}
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