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 +1,60 @@
+---
+tags:
+- autonlp
+- question-answering
+language: unk
+widget:
+- text: "Who loves AutoNLP?"
+  context: "Everyone loves AutoNLP"
+datasets:
+- teacookies/autonlp-data-roberta-base-squad2
+co2_eq_emissions: 70.20260764805424
+---
+
+# Model Trained Using AutoNLP
+
+- Problem type: Extractive Question Answering
+- Model ID: 24465521
+- CO2 Emissions (in grams): 70.20260764805424
+
+## Validation Metrics
+
+- Loss: 0.6295848488807678
+
+## Usage
+
+You can use cURL to access this model:
+
+```
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"question": "Who loves AutoNLP?", "context": "Everyone loves AutoNLP"}' https://api-inference.huggingface.co/models/teacookies/autonlp-roberta-base-squad2-24465521
+```
+
+Or Python API:
+
+```
+import torch
+
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer
+
+model = AutoModelForQuestionAnswering.from_pretrained("teacookies/autonlp-roberta-base-squad2-24465521", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("teacookies/autonlp-roberta-base-squad2-24465521", use_auth_token=True)
+
+from transformers import BertTokenizer, BertForQuestionAnswering
+
+question, text = "Who loves AutoNLP?", "Everyone loves AutoNLP"
+
+inputs = tokenizer(question, text, return_tensors='pt')
+
+start_positions = torch.tensor([1])
+
+end_positions = torch.tensor([3])
+
+outputs = model(**inputs, start_positions=start_positions, end_positions=end_positions)
+
+loss = outputs.loss
+
+start_scores = outputs.start_logits
+
+end_scores = outputs.end_logits
+```

config.json

@@ -0,0 +1,31 @@
+{
+  "_name_or_path": "AutoNLP",
+  "architectures": [
+    "XLMRobertaForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "language": "english",
+  "layer_norm_eps": 1e-05,
+  "max_length": 512,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "name": "XLMRoberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.8.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e739edef143532cb79aea11509271dc66831924e031ccc155a4dc39e79c73d4c
+size 1109903089

sample_input.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d22c4b0703481a327f22e50409860beb1b6023d79cf85865f3887a5a03c86122
+size 2527

sentencepiece.bpe.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
+size 5069051

special_tokens_map.json

@@ -0,0 +1 @@
+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}

tokenizer_config.json

@@ -0,0 +1 @@
+{"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "do_lower_case": false, "model_max_length": 512, "full_tokenizer_file": null, "special_tokens_map_file": "/root/.cache/huggingface/transformers/b285d730ad6193f7e96b41152fbc5fb05620f0961f6f513e2d36868dfb1eb2a7.0dc5b1041f62041ebbd23b1297f2f573769d5c97d8b7c28180ec86b8f6185aa8", "name_or_path": "AutoNLP", "sp_model_kwargs": {}, "tokenizer_class": "XLMRobertaTokenizer"}