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Add new SentenceTransformer model.

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README.md ADDED
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+ ---
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+ library_name: light-embed
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+ pipeline_tag: sentence-similarity
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+ tags:
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+ - sentence-transformers
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+ - feature-extraction
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+ - sentence-similarity
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+
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+ ---
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+
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+ # LightEmbed/all-MiniLM-L6-v2-onnx
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+
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+ This is the ONNX version of the Sentence Transformers model sentence-transformers/all-MiniLM-L6-v2 (https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) for sentence embedding, optimized for speed and lightweight performance. By utilizing onnxruntime and tokenizers instead of heavier libraries like sentence-transformers and transformers, this version ensures a smaller library size and faster execution. Below are the details of the model:
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+ - Base model: sentence-transformers/all-MiniLM-L6-v2
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+ - Embedding dimension: 384
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+ - Max sequence length: 256
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+ - File size on disk: 0.08 GB
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+ - Pooling incorporated: Yes
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+
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+ This ONNX model consists all components in the original sentence transformer model:
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+ Transformer, Pooling, Normalize
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+
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+ <!--- Describe your model here -->
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+
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+ ## Usage (LightEmbed)
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+
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+ Using this model becomes easy when you have [LightEmbed](https://pypi.org/project/light-embed/) installed:
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+
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+ ```
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+ pip install -U light-embed
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+ ```
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+
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+ Then you can use the model using the original model name like this:
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+
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+ ```python
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+ from light_embed import TextEmbedding
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+ sentences = [
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+ "This is an example sentence",
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+ "Each sentence is converted"
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+ ]
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+
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+ model = TextEmbedding('sentence-transformers/all-MiniLM-L6-v2')
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+ embeddings = model.encode(sentences)
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+ print(embeddings)
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+ ```
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+
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+ Then you can use the model using onnx model name like this:
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+
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+ ```python
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+ from light_embed import TextEmbedding
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+ sentences = [
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+ "This is an example sentence",
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+ "Each sentence is converted"
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+ ]
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+
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+ model = TextEmbedding('LightEmbed/all-MiniLM-L6-v2-onnx')
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+ embeddings = model.encode(sentences)
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+ print(embeddings)
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+ ```
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+
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+ ## Citing & Authors
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+
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+ Binh Nguyen / [email protected]
config.json ADDED
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+ {
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+ "_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
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+ "architectures": [
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+ "BertModel"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 384,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 1536,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.8.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
config_sentence_transformers.json ADDED
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+ {
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+ "__version__": {
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+ "sentence_transformers": "2.0.0",
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+ "transformers": "4.6.1",
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+ "pytorch": "1.8.1"
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+ }
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+ }
model.onnx ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:3cc4e13264bea58a3257cec9821637bcab95e687137a07152e08ab3af37f809f
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+ size 90446240
special_tokens_map.json ADDED
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+ {
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+ "cls_token": {
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+ "content": "[CLS]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "mask_token": {
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+ "content": "[MASK]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "pad_token": {
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+ "content": "[PAD]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "sep_token": {
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+ "content": "[SEP]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "unk_token": {
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+ "content": "[UNK]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ }
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+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ {
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+ "added_tokens_decoder": {
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+ "0": {
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+ "content": "[PAD]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "100": {
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+ "content": "[UNK]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "101": {
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+ "content": "[CLS]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "102": {
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+ "content": "[SEP]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "103": {
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+ "content": "[MASK]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ }
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+ },
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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": true,
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+ "mask_token": "[MASK]",
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+ "max_length": 128,
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+ "model_max_length": 256,
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+ "never_split": null,
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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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+ }
vocab.txt ADDED
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