Text Classification
sentence-transformers
Safetensors
English
bert
ren
secnd
selective-classification
calibration
human-in-the-loop
text-embeddings-inference
Instructions to use Secnd-AI/ren with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Secnd-AI/ren with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Secnd-AI/ren") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Add reader checkpoint ic-ettin-400m-s6000-near-wide-fine-seed1
Browse files- reader/encoder/config.json +85 -0
- reader/encoder/model.safetensors +3 -0
- reader/encoder/tokenizer.json +0 -0
- reader/encoder/tokenizer_config.json +17 -0
- reader/scorer.pt +3 -0
reader/encoder/config.json
ADDED
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{
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"architectures": [
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"ModernBertModel"
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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": 50281,
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"causal_mask": false,
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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": 50282,
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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": 1024,
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"initializer_cutoff_factor": 2.0,
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"initializer_range": 0.02,
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"intermediate_size": 2624,
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"is_causal": false,
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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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"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": 7999,
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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": 16,
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"num_hidden_layers": 28,
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"pad_token_id": 50283,
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"position_embedding_type": "sans_pos",
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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": 160000.0,
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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": "5.21.0",
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"vocab_size": 50368
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}
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reader/encoder/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5396a0be1ab8bbca221641c61018ab62528f9884ddcabf65d3599d8824f8d949
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size 1579143688
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reader/encoder/tokenizer.json
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The diff for this file is too large to render.
See raw diff
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reader/encoder/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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"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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"attention_mask"
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],
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"model_max_length": 8192,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "[UNK]"
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}
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reader/scorer.pt
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:9d2a0401df24d8751a525851927bd49ca7c7c6346b45418ac21ee1fc349225f0
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size 4213385
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