Token Classification
Scikit-learn
PyTorch
TensorBoard
Safetensors
Transformers
English
distilbert
ner
mlflow
openchs
Eval Results (legacy)
Instructions to use openchs/ner_distillbert_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use openchs/ner_distillbert_v1 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("openchs/ner_distillbert_v1", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Transformers
How to use openchs/ner_distillbert_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="openchs/ner_distillbert_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("openchs/ner_distillbert_v1") model = AutoModelForTokenClassification.from_pretrained("openchs/ner_distillbert_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForTokenClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "dim": 768, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "hidden_dim": 3072, | |
| "id2label": { | |
| "0": "CALLER", | |
| "1": "PERPETRATOR", | |
| "2": "GENDER", | |
| "3": "VICTIM", | |
| "4": "AGE", | |
| "5": "LOCATION", | |
| "6": "INCIDENT_TYPE", | |
| "7": "O", | |
| "8": "COUNSELOR" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "AGE": 4, | |
| "CALLER": 0, | |
| "COUNSELOR": 8, | |
| "GENDER": 2, | |
| "INCIDENT_TYPE": 6, | |
| "LOCATION": 5, | |
| "O": 7, | |
| "PERPETRATOR": 1, | |
| "VICTIM": 3 | |
| }, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 12, | |
| "n_layers": 6, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": false, | |
| "tie_weights_": true, | |
| "transformers_version": "4.56.2", | |
| "vocab_size": 28996 | |
| } | |