Text Classification
Transformers
Safetensors
modernbert
mmbert
sentiment-analysis
twitter
multilingual
text-embeddings-inference
Instructions to use Ido-shraga/mmbert-base-sentiment-adapted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ido-shraga/mmbert-base-sentiment-adapted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ido-shraga/mmbert-base-sentiment-adapted")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ido-shraga/mmbert-base-sentiment-adapted") model = AutoModelForSequenceClassification.from_pretrained("Ido-shraga/mmbert-base-sentiment-adapted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Make config and tokenizer loadable by transformers v4
Browse files- tokenizer_config.json +7 -10
tokenizer_config.json
CHANGED
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{
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"backend": "tokenizers",
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"bos_token": "<bos>",
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"clean_up_tokenization_spaces": false,
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"cls_token": "<bos>",
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"eos_token": "<eos>",
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"extra_special_tokens": [
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"<start_of_turn>",
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"<end_of_turn>"
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],
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"is_local": false,
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"local_files_only": false,
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"mask_token": "<mask>",
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"model_input_names": [
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"input_ids",
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"padding_side": "right",
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"sep_token": "<eos>",
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"spaces_between_special_tokens": false,
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"tokenizer_class": "
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"unk_token": "<unk>"
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{
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"bos_token": "<bos>",
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"clean_up_tokenization_spaces": false,
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"cls_token": "<bos>",
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"eos_token": "<eos>",
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"mask_token": "<mask>",
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"model_input_names": [
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"input_ids",
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"padding_side": "right",
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"sep_token": "<eos>",
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"spaces_between_special_tokens": false,
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"tokenizer_class": "PreTrainedTokenizerFast",
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"unk_token": "<unk>",
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"additional_special_tokens": [
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"<start_of_turn>",
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"<end_of_turn>"
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]
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}
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