.gitattributes

@@ -6,4 +6,3 @@
 *.tar.gz filter=lfs diff=lfs merge=lfs -text
 *.ot filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,97 +0,0 @@
----
-language: en
-license: cc-by-4.0
-datasets:
-- squad_v2
-model-index:
-- name: deepset/bert-large-uncased-whole-word-masking-squad2
-  results:
-  - task:
-      type: question-answering
-      name: Question Answering
-    dataset:
-      name: squad_v2
-      type: squad_v2
-      config: squad_v2
-      split: validation
-    metrics:
-    - type: exact_match
-      value: 80.8846
-      name: Exact Match
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2E5ZGNkY2ExZWViZGEwNWE3OGRmMWM2ZmE4ZDU4ZDQ1OGM3ZWE0NTVmZjFmYmZjZmJmNjJmYTc3NTM3OTk3OSIsInZlcnNpb24iOjF9.aSblF4ywh1fnHHrN6UGL392R5KLaH3FCKQlpiXo_EdQ4XXEAENUCjYm9HWDiFsgfSENL35GkbSyz_GAhnefsAQ
-    - type: f1
-      value: 83.8765
-      name: F1
-      verified: true
-      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGFlNmEzMTk2NjRkNTI3ZTk3ZTU1NWNlYzIyN2E0ZDFlNDA2ZjYwZWJlNThkMmRmMmE0YzcwYjIyZDM5NmRiMCIsInZlcnNpb24iOjF9.-rc2_Bsp_B26-o12MFYuAU0Ad2Hg9PDx7Preuk27WlhYJDeKeEr32CW8LLANQABR3Mhw2x8uTYkEUrSDMxxLBw
----
-
-# bert-large-uncased-whole-word-masking-squad2
-
-This is a berta-large model, fine-tuned using the SQuAD2.0 dataset for the task of question answering.
-
-## Overview
-**Language model:** bert-large  
-**Language:** English  
-**Downstream-task:** Extractive QA  
-**Training data:** SQuAD 2.0  
-**Eval data:** SQuAD 2.0  
-**Code:**  See [an example QA pipeline on Haystack](https://haystack.deepset.ai/tutorials/first-qa-system)  
-
-## Usage
-
-### In Haystack
-Haystack is an NLP framework by deepset. You can use this model in a Haystack pipeline to do question answering at scale (over many documents). To load the model in [Haystack](https://github.com/deepset-ai/haystack/):
-```python
-reader = FARMReader(model_name_or_path="deepset/bert-large-uncased-whole-word-masking-squad2")
-# or 
-reader = TransformersReader(model_name_or_path="FILL",tokenizer="deepset/bert-large-uncased-whole-word-masking-squad2")
-```
-
-### In Transformers
-```python
-from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
-
-model_name = "deepset/bert-large-uncased-whole-word-masking-squad2"
-
-# a) Get predictions
-nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
-QA_input = {
-    'question': 'Why is model conversion important?',
-    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
-}
-res = nlp(QA_input)
-
-# b) Load model & tokenizer
-model = AutoModelForQuestionAnswering.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-```
-
-## About us
-<div class="grid lg:grid-cols-2 gap-x-4 gap-y-3">
-    <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
-         <img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/deepset-logo-colored.png" class="w-40"/>
-     </div>
-     <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
-         <img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/haystack-logo-colored.png" class="w-40"/>
-     </div>
-</div>
-
-[deepset](http://deepset.ai/) is the company behind the open-source NLP framework [Haystack](https://haystack.deepset.ai/) which is designed to help you build production ready NLP systems that use: Question answering, summarization, ranking etc.
-
-
-Some of our other work: 
-- [Distilled roberta-base-squad2 (aka "tinyroberta-squad2")]([https://huggingface.co/deepset/tinyroberta-squad2)
-- [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
-- [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
-
-## Get in touch and join the Haystack community
-
-<p>For more info on Haystack, visit our <strong><a href="https://github.com/deepset-ai/haystack">GitHub</a></strong> repo and <strong><a href="https://docs.haystack.deepset.ai">Documentation</a></strong>. 
-
-We also have a <strong><a class="h-7" href="https://haystack.deepset.ai/community">Discord community open to everyone!</a></strong></p>
-
-[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Discord](https://haystack.deepset.ai/community/join) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)
-
-By the way: [we're hiring!](http://www.deepset.ai/jobs)

config.json

@@ -3,21 +3,45 @@
     "BertForQuestionAnswering"
   ],
   "attention_probs_dropout_prob": 0.1,
+  "do_sample": false,
   "finetuning_task": "squad2",
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1"
+  },
   "initializer_range": 0.02,
   "intermediate_size": 4096,
+  "is_decoder": false,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1
+  },
   "language": "english",
   "layer_norm_eps": 1e-12,
+  "length_penalty": 1.0,
+  "max_length": 20,
   "max_position_embeddings": 512,
   "model_type": "bert",
   "name": "Bert",
   "num_attention_heads": 16,
+  "num_beams": 1,
   "num_hidden_layers": 24,
+  "num_labels": 2,
+  "num_return_sequences": 1,
+  "output_attentions": false,
+  "output_hidden_states": false,
   "output_past": true,
   "pad_token_id": 0,
+  "pruned_heads": {},
+  "repetition_penalty": 1.0,
+  "temperature": 1.0,
+  "top_k": 50,
+  "top_p": 1.0,
+  "torchscript": false,
   "type_vocab_size": 2,
+  "use_bfloat16": false,
   "vocab_size": 30522
 }

modelcard.json

@@ -0,0 +1,11 @@
+{
+  "caveats_and_recommendations": {},
+  "ethical_considerations": {},
+  "evaluation_data": {},
+  "factors": {},
+  "intended_use": {},
+  "metrics": {},
+  "model_details": {},
+  "quantitative_analyses": {},
+  "training_data": {}
+}