Commit From AutoNLP

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags: autonlp
+language: unk
+widget:
+- text: "I love AutoNLP 🤗"
+datasets:
+- pediberto/autonlp-data-testing
+co2_eq_emissions: 12.994518654810642
+---
+
+# Model Trained Using AutoNLP
+
+- Problem type: Binary Classification
+- Model ID: 504313966
+- CO2 Emissions (in grams): 12.994518654810642
+
+## Validation Metrics
+
+- Loss: 0.19673296809196472
+- Accuracy: 0.9398032027783138
+- Precision: 0.9133115705476967
+- Recall: 0.9718255499807025
+- AUC: 0.985316873222122
+- F1: 0.9416604338070308
+
+## Usage
+
+You can use cURL to access this model:
+
+```
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoNLP"}' https://api-inference.huggingface.co/models/pediberto/autonlp-testing-504313966
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("pediberto/autonlp-testing-504313966", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("pediberto/autonlp-testing-504313966", use_auth_token=True)
+
+inputs = tokenizer("I love AutoNLP", return_tensors="pt")
+
+outputs = model(**inputs)
+```

added_tokens.json

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+{"<mask>": 64000}

config.json

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+{
+  "_name_or_path": "AutoNLP",
+  "_num_labels": 2,
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "misleading",
+    "1": "ok"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "misleading": 0,
+    "ok": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "max_length": 128,
+  "max_position_embeddings": 130,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "tokenizer_class": "BertweetTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.15.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 64001
+}

pytorch_model.bin

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sample_input.pkl

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special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}

tokenizer_config.json

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+{"normalization": true, "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "AutoNLP", "tokenizer_class": "BertweetTokenizer"}