Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use redevaaa/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redevaaa/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="redevaaa/test2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("redevaaa/test2") model = AutoModelForTokenClassification.from_pretrained("redevaaa/test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from redevaaa/test2: direct link, hf CLI and curl.
- Browser
- Download file 1.52 kB
-
https://huggingface.co/redevaaa/test2/resolve/main/config.json
- Command line
-
hf download hf://redevaaa/test2/config.json
-
curl -L -o config.json https://huggingface.co/redevaaa/test2/resolve/main/config.json
1.52 kB
| { | |
| "_name_or_path": "bert-base-cased", | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "O", | |
| "1": "B-MethodName", | |
| "10": "I-MetricValue", | |
| "11": "B-TaskName", | |
| "12": "I-TaskName", | |
| "13": "B-DatasetName", | |
| "14": "I-DatasetName", | |
| "2": "I-MethodName", | |
| "3": "B-HyperparameterName", | |
| "4": "I-HyperparameterName", | |
| "5": "B-HyperparameterValue", | |
| "6": "I-HyperparameterValue", | |
| "7": "B-MetricName", | |
| "8": "I-MetricName", | |
| "9": "B-MetricValue" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "B-DatasetName": "13", | |
| "B-HyperparameterName": "3", | |
| "B-HyperparameterValue": "5", | |
| "B-MethodName": "1", | |
| "B-MetricName": "7", | |
| "B-MetricValue": "9", | |
| "B-TaskName": "11", | |
| "I-DatasetName": "14", | |
| "I-HyperparameterName": "4", | |
| "I-HyperparameterValue": "6", | |
| "I-MethodName": "2", | |
| "I-MetricName": "8", | |
| "I-MetricValue": "10", | |
| "I-TaskName": "12", | |
| "O": "0" | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.23.1", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 28996 | |
| } | |