Add Neuron-optimized files for oxyapi/albert-moderation-001
Browse files🤖 Neuron Export Bot: Adding AWS Neuron-optimized model files.
Original model: [oxyapi/albert-moderation-001](https://huggingface.co/oxyapi/albert-moderation-001)
Task: text-classification
Generated by: [badaoui](https://huggingface.co/badaoui)
Generated using: [Optimum Neuron Compiler Space](https://huggingface.co/spaces/optimum/neuron-export)
These files have been pre-compiled for AWS Neuron devices (Inferentia/Trainium) and should provide improved inference performance.
- .gitattributes +1 -0
- README.md +38 -0
- config.json +72 -0
- model.neuron +3 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +56 -0
- vocab.txt +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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model.neuron filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags:
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- neuron
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- optimized
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- aws-neuron
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- text-classification
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base_model: oxyapi/albert-moderation-001
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---
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# Neuron-Optimized oxyapi/albert-moderation-001
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This repository contains AWS Neuron-optimized files for [oxyapi/albert-moderation-001](https://huggingface.co/oxyapi/albert-moderation-001).
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## Model Details
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- **Base Model**: [oxyapi/albert-moderation-001](https://huggingface.co/oxyapi/albert-moderation-001)
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- **Task**: text-classification
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- **Optimization**: AWS Neuron compilation
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- **Generated by**: [badaoui](https://huggingface.co/badaoui)
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- **Generated using**: [Optimum Neuron Compiler Space](https://huggingface.co/spaces/optimum/neuron-export)
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## Usage
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This model has been optimized for AWS Neuron devices (Inferentia/Trainium). To use it:
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```python
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from optimum.neuron import NeuronModelForSequenceClassification
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model = NeuronModelForSequenceClassification.from_pretrained("badaoui/oxyapi-albert-moderation-001-neuron")
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```
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## Performance
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These files are pre-compiled for AWS Neuron devices and should provide improved inference performance compared to the original model when deployed on Inferentia or Trainium instances.
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## Original Model
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For the original model, training details, and more information, please visit: [oxyapi/albert-moderation-001](https://huggingface.co/oxyapi/albert-moderation-001)
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config.json
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{
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "harassment",
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"1": "harassment/threatening",
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"2": "sexual",
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"3": "hate",
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"4": "hate/threatening",
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"5": "self-harm/intent",
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"6": "self-harm/instructions",
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"7": "self-harm",
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"8": "sexual/minors",
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"9": "violence",
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"10": "violence/graphic"
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},
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"initializer_range": 0.02,
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"label2id": {
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"harassment": 0,
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"harassment/threatening": 1,
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"hate": 3,
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"hate/threatening": 4,
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"self-harm": 7,
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"self-harm/instructions": 6,
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"self-harm/intent": 5,
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"sexual": 2,
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"sexual/minors": 8,
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"violence": 9,
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"violence/graphic": 10
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"neuron": {
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"auto_cast": "matmul",
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"auto_cast_type": "bf16",
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"compiler_type": "neuronx-cc",
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"compiler_version": "2.21.18209.0+043b1bf7",
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"disable_fallback": false,
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"disable_fast_relayout": false,
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"dynamic_batch_size": false,
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"float_dtype": "fp32",
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"inline_weights_to_neff": true,
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"instance_type": "inf2",
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"int_dtype": "int64",
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"model_type": "distilbert",
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"optlevel": "2",
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"output_attentions": false,
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"output_hidden_states": false,
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"static_batch_size": 1,
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"static_sequence_length": 128,
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"task": "text-classification",
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"tensor_parallel_size": 1
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},
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"pad_token_id": 0,
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"problem_type": "multi_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"torchscript": true,
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"transformers_version": "4.55.4",
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"vocab_size": 30522
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}
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model.neuron
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version https://git-lfs.github.com/spec/v1
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oid sha256:363316bf8b4145995026da7cfed48c78b855d5a4647f38e3037f5e352a78db9b
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size 156251194
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special_tokens_map.json
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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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}
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tokenizer.json
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See raw diff
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tokenizer_config.json
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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": false,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"extra_special_tokens": {},
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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| 54 |
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
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