Delete multi-label_8_sent_v3_1

multi-label_8_sent_v3_1/1_Pooling/config.json

@@ -1,7 +0,0 @@
-{
-  "word_embedding_dimension": 768,
-  "pooling_mode_cls_token": false,
-  "pooling_mode_mean_tokens": true,
-  "pooling_mode_max_tokens": false,
-  "pooling_mode_mean_sqrt_len_tokens": false
-}

multi-label_8_sent_v3_1/README.md

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----
-license: apache-2.0
-tags:
-- setfit
-- sentence-transformers
-- text-classification
-pipeline_tag: text-classification
----
-
-# multi-label_8_sent_v3_1
-
-This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
-
-1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
-2. Training a classification head with features from the fine-tuned Sentence Transformer.
-
-## Usage
-
-To use this model for inference, first install the SetFit library:
-
-```bash
-python -m pip install setfit
-```
-
-You can then run inference as follows:
-
-```python
-from setfit import SetFitModel
-
-# Download from Hub and run inference
-model = SetFitModel.from_pretrained("multi-label_8_sent_v3_1")
-# Run inference
-preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
-```
-
-## BibTeX entry and citation info
-
-```bibtex
-@article{https://doi.org/10.48550/arxiv.2209.11055,
-doi = {10.48550/ARXIV.2209.11055},
-url = {https://arxiv.org/abs/2209.11055},
-author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
-keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
-title = {Efficient Few-Shot Learning Without Prompts},
-publisher = {arXiv},
-year = {2022},
-copyright = {Creative Commons Attribution 4.0 International}
-}
-```

multi-label_8_sent_v3_1/config.json

@@ -1,24 +0,0 @@
-{
-  "_name_or_path": "C:\\Users\\myoxon/.cache\\torch\\sentence_transformers\\sentence-transformers_paraphrase-mpnet-base-v2\\",
-  "architectures": [
-    "MPNetModel"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "bos_token_id": 0,
-  "eos_token_id": 2,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-05,
-  "max_position_embeddings": 514,
-  "model_type": "mpnet",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "pad_token_id": 1,
-  "relative_attention_num_buckets": 32,
-  "torch_dtype": "float32",
-  "transformers_version": "4.25.1",
-  "vocab_size": 30527
-}

multi-label_8_sent_v3_1/config_sentence_transformers.json

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-{
-  "__version__": {
-    "sentence_transformers": "2.0.0",
-    "transformers": "4.7.0",
-    "pytorch": "1.9.0+cu102"
-  }
-}

multi-label_8_sent_v3_1/model_head.pkl

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-size 52905

multi-label_8_sent_v3_1/modules.json

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-[
-  {
-    "idx": 0,
-    "name": "0",
-    "path": "",
-    "type": "sentence_transformers.models.Transformer"
-  },
-  {
-    "idx": 1,
-    "name": "1",
-    "path": "1_Pooling",
-    "type": "sentence_transformers.models.Pooling"
-  }
-]

multi-label_8_sent_v3_1/pytorch_model.bin

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multi-label_8_sent_v3_1/sentence_bert_config.json

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-{
-  "max_seq_length": 512,
-  "do_lower_case": false
-}

multi-label_8_sent_v3_1/special_tokens_map.json

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-{
-  "bos_token": "<s>",
-  "cls_token": "<s>",
-  "eos_token": "</s>",
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-    "content": "<mask>",
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-  },
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-}

multi-label_8_sent_v3_1/tokenizer_config.json

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-{
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