Instructions to use Monda/task1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Monda/task1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Monda/task1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Monda/task1") model = AutoModelForSequenceClassification.from_pretrained("Monda/task1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,856 Bytes
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"added_tokens_decoder": {
"0": {
"content": "[PAD]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "[UNK]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "[CLS]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"3": {
"content": "[SEP]",
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"special": true
},
"4": {
"content": "[MASK]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"5": {
"content": "[رابط]",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": true,
"special": true
},
"6": {
"content": "[بريد]",
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"single_word": true,
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},
"7": {
"content": "[مستخدم]",
"lstrip": false,
"normalized": true,
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"single_word": true,
"special": true
}
},
"clean_up_tokenization_spaces": false,
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": false,
"extra_special_tokens": {},
"mask_token": "[MASK]",
"max_len": 512,
"model_max_length": 512,
"never_split": [
"[بريد]",
"[مستخدم]",
"[رابط]"
],
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
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