Text Classification
Transformers
Safetensors
English
modernbert
sentiment-analysis
sentiment
sst-2
sst2
reviews
english
positive-negative
distilbert-sst2-alternative
text-embeddings-inference
Instructions to use AnkitAI/Sensible-ModernBERT-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/Sensible-ModernBERT-Sentiment-Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/Sensible-ModernBERT-Sentiment-Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnkitAI/Sensible-ModernBERT-Sentiment-Analysis") model = AutoModelForSequenceClassification.from_pretrained("AnkitAI/Sensible-ModernBERT-Sentiment-Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ModernBERT SST-2 sentiment: 0.9461 on official validation
Browse files- config.json +87 -0
config.json
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{
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"architectures": [
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"ModernBertForSequenceClassification"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": null,
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"classifier_activation": "gelu",
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"classifier_bias": false,
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"classifier_dropout": 0.0,
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"classifier_pooling": "mean",
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"cls_token_id": 50281,
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"decoder_bias": true,
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"deterministic_flash_attn": false,
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"dtype": "float32",
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"embedding_dropout": 0.0,
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"eos_token_id": null,
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"global_attn_every_n_layers": 3,
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"gradient_checkpointing": false,
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"hidden_activation": "gelu",
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"hidden_size": 768,
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"id2label": {
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"0": "negative",
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"1": "positive"
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},
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"initializer_cutoff_factor": 2.0,
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"initializer_range": 0.02,
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"intermediate_size": 1152,
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"label2id": {
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"negative": 0,
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"positive": 1
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},
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"layer_norm_eps": 1e-05,
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"layer_types": [
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention"
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],
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"local_attention": 128,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"mlp_dropout": 0.0,
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"model_type": "modernbert",
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"norm_bias": false,
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"norm_eps": 1e-05,
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"num_attention_heads": 12,
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"num_hidden_layers": 22,
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"pad_token_id": 50283,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"rope_parameters": {
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"full_attention": {
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"rope_theta": 160000.0,
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"rope_type": "default"
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},
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"sliding_attention": {
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"rope_theta": 10000.0,
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"rope_type": "default"
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}
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},
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"sep_token_id": 50282,
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"sparse_pred_ignore_index": -100,
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"sparse_prediction": false,
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"tie_word_embeddings": true,
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"transformers_version": "5.13.1",
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"use_cache": false,
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"vocab_size": 50368
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}
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