Commit From AutoTrain

.gitattributes

@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.tar.gz filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,49 @@
+---
+tags:
+- autotrain
+- token-classification
+language:
+- de
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- peanutacake/autotrain-data-ajmc_ner_de
+co2_eq_emissions:
+  emissions: 1.2159543426004786
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Entity Extraction
+- Model ID: 53413125973
+- CO2 Emissions (in grams): 1.2160
+
+## Validation Metrics
+
+- Loss: 0.109
+- Accuracy: 0.976
+- Precision: 0.000
+- Recall: 0.000
+- F1: 0.000
+
+## 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 AutoTrain"}' https://api-inference.huggingface.co/models/peanutacake/autotrain-ajmc_ner_de-53413125973
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForTokenClassification, AutoTokenizer
+
+model = AutoModelForTokenClassification.from_pretrained("peanutacake/autotrain-ajmc_ner_de-53413125973", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("peanutacake/autotrain-ajmc_ner_de-53413125973", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

@@ -0,0 +1,61 @@
+{
+  "_name_or_path": "AutoTrain",
+  "_num_labels": 12,
+  "architectures": [
+    "ElectraForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "embedding_size": 1024,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "10",
+    "3": "11",
+    "4": "12",
+    "5": "2",
+    "6": "3",
+    "7": "4",
+    "8": "5",
+    "9": "6",
+    "10": "7",
+    "11": "9"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "10": 2,
+    "11": 3,
+    "12": 4,
+    "2": 5,
+    "3": 6,
+    "4": 7,
+    "5": 8,
+    "6": 9,
+    "7": 10,
+    "9": 11
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 128,
+  "max_position_embeddings": 512,
+  "model_type": "electra",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "summary_activation": "gelu",
+  "summary_last_dropout": 0.1,
+  "summary_type": "first",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.28.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31102
+}

pytorch_model.bin

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special_tokens_map.json

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

tokenizer.json

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+size 729326

tokenizer_config.json

@@ -0,0 +1,16 @@
+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "max_len": 512,
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": false,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "ElectraTokenizer",
+  "unk_token": "[UNK]"
+}