update model
Browse files- README.md +8 -8
- config.json +52 -30
- model.safetensors +2 -2
- onnx/model.onnx +2 -2
- onnx/model_bnb4.onnx +2 -2
- onnx/model_fp16.onnx +2 -2
- onnx/model_int8.onnx +2 -2
- onnx/model_q4.onnx +2 -2
- onnx/model_q4f16.onnx +2 -2
- onnx/model_quantized.onnx +2 -2
- onnx/model_uint8.onnx +2 -2
- quantize_config.json +2 -3
- tokenizer_config.json +1 -0
README.md
CHANGED
@@ -3,7 +3,7 @@ language: en
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thumbnail: https://huggingface.co/front/thumbnails/google.png
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license: apache-2.0
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base_model:
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- cross-encoder/ms-marco-
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pipeline_tag: text-classification
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library_name: transformers
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metrics:
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## Cross-Encoder for MS Marco with TinyBert
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This is a fine-tuned version of the model checkpointed at [cross-encoder/ms-marco-
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It was fine-tuned on html tags and labels generated using [Fathom](https://mozilla.github.io/fathom/commands/label.html).
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@@ -31,18 +31,18 @@ classifier = pipeline(
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)
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print(
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classifier('
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)
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```
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## Model Training Info
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```python
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HyperParameters
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'learning_rate':
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'num_train_epochs':
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'weight_decay': 0.
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'per_device_train_batch_size': 32
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}
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```
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thumbnail: https://huggingface.co/front/thumbnails/google.png
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license: apache-2.0
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base_model:
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+
- cross-encoder/ms-marco-MiniLM-L-4-v2
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pipeline_tag: text-classification
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library_name: transformers
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metrics:
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## Cross-Encoder for MS Marco with TinyBert
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+
This is a fine-tuned version of the model checkpointed at [cross-encoder/ms-marco-MiniLM-L-4-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-4-v2).
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It was fine-tuned on html tags and labels generated using [Fathom](https://mozilla.github.io/fathom/commands/label.html).
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)
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print(
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classifier('Card information input Card number cc-number <SEP> <SEP> input First name <SEP> <SEP>')
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)
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```
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## Model Training Info
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```python
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HyperParameters = {
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'learning_rate': 2.3878733582558547e-05,
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'num_train_epochs': 21,
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'weight_decay': 0.0005288040458920454,
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'per_device_train_batch_size': 32
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}
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```
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config.json
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@@ -1,6 +1,6 @@
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{
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"_attn_implementation_autoset": true,
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"_name_or_path": "/content/cross-encoder/ms-marco-
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"architectures": [
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"BertForSequenceClassification"
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],
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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":
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"id2label": {
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"0": "
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"1": "
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"2": "
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"3": "
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"4": "cc-
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"5": "cc-
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"6": "cc-
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"7": "
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"8": "
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"9": "
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"10": "
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"11": "
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},
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"initializer_range": 0.02,
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"intermediate_size":
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"label2id": {
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"
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"
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"
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"
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"cc-
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"cc-
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"cc-
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"
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"
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},
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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":
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"num_hidden_layers":
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"sbert_ce_default_activation_function": "torch.nn.modules.linear.Identity",
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"transformers_version": "4.46.
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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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{
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"_attn_implementation_autoset": true,
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"_name_or_path": "/content/cross-encoder/ms-marco-MiniLM-L-4-v2",
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"architectures": [
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"BertForSequenceClassification"
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],
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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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"id2label": {
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"0": "address-level1",
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"1": "address-level2",
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"2": "address-line1",
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"3": "address-line2",
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"4": "cc-csc",
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"5": "cc-exp",
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"6": "cc-exp-month",
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"7": "cc-exp-year",
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"8": "cc-name",
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"9": "cc-number",
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"10": "cc-type",
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"11": "country-name",
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"12": "current-password",
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"13": "email",
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"14": "family-name",
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"15": "given-name",
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"16": "name",
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"17": "new-password",
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"18": "organization",
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"19": "other",
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"20": "postal-code",
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"21": "street-address",
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"22": "tel"
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},
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"initializer_range": 0.02,
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"intermediate_size": 1536,
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"label2id": {
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"address-level1": 0,
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"address-level2": 1,
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"address-line1": 2,
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"address-line2": 3,
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"cc-csc": 4,
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"cc-exp": 5,
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"cc-exp-month": 6,
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"cc-exp-year": 7,
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"cc-name": 8,
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"cc-number": 9,
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"cc-type": 10,
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"country-name": 11,
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"current-password": 12,
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"email": 13,
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"family-name": 14,
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"given-name": 15,
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"name": 16,
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"new-password": 17,
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"organization": 18,
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"other": 19,
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"postal-code": 20,
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"street-address": 21,
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"tel": 22
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},
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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": 4,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"sbert_ce_default_activation_function": "torch.nn.modules.linear.Identity",
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"transformers_version": "4.46.1",
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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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model.safetensors
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onnx/model.onnx
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onnx/model_bnb4.onnx
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onnx/model_fp16.onnx
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onnx/model_int8.onnx
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onnx/model_q4.onnx
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onnx/model_q4f16.onnx
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onnx/model_quantized.onnx
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onnx/model_uint8.onnx
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quantize_config.json
CHANGED
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"q4f16",
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"bnb4"
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],
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-
"per_channel":
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"reduce_range": true,
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"block_size": null,
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"is_symmetric": true,
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"accuracy_level": null,
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"quant_type": 1
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"op_block_list": null
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}
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"q4f16",
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"bnb4"
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],
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"per_channel": true,
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"reduce_range": true,
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"block_size": null,
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"is_symmetric": true,
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"accuracy_level": null,
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"quant_type": 1
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}
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tokenizer_config.json
CHANGED
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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": 512,
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"model_max_length": 512,
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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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"extra_special_tokens": {},
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"mask_token": "[MASK]",
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"max_length": 512,
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"model_max_length": 512,
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