Commit From AutoNLP

.gitattributes

@@ -25,3 +25,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.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

@@ -0,0 +1,46 @@
+---
+tags: autonlp
+language: unk
+widget:
+- text: "I love AutoNLP 🤗"
+datasets:
+- lidiia/autonlp-data-trans_class_arg
+co2_eq_emissions: 0.9756221672668951
+---
+
+# Model Trained Using AutoNLP
+
+- Problem type: Binary Classification
+- Model ID: 32957902
+- CO2 Emissions (in grams): 0.9756221672668951
+
+## Validation Metrics
+
+- Loss: 0.2765039801597595
+- Accuracy: 0.8939828080229226
+- Precision: 0.7757009345794392
+- Recall: 0.8645833333333334
+- AUC: 0.9552659749670619
+- F1: 0.8177339901477833
+
+## 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/lidiia/autonlp-trans_class_arg-32957902
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("lidiia/autonlp-trans_class_arg-32957902", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("lidiia/autonlp-trans_class_arg-32957902", use_auth_token=True)
+
+inputs = tokenizer("I love AutoNLP", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

@@ -0,0 +1,36 @@
+{
+  "_name_or_path": "AutoNLP",
+  "_num_labels": 2,
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "0.0",
+    "1": "1.0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0.0": 0,
+    "1.0": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 128,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "transformers_version": "4.8.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30000
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f5728ec21f2794c32fb228a1f9d6769443837115be3b6ec42966b969fdeba163
+size 436415661

sample_input.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a8dc4ce992529feaedf3add914fefb23646908a7e7906f5cd8077172bc4ba22b
+size 4384

special_tokens_map.json

@@ -0,0 +1 @@
+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

@@ -0,0 +1 @@
+{"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "AutoNLP", "tokenizer_class": "BertTokenizer"}