Instructions to use pki/ner-cybersecurity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use pki/ner-cybersecurity with spaCy:
!pip install https://huggingface.co/pki/ner-cybersecurity/resolve/main/ner-cybersecurity-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("ner-cybersecurity") # Importing as module. import ner-cybersecurity nlp = ner-cybersecurity.load() - Notebooks
- Google Colab
- Kaggle
Download parser/cfg from pki/ner-cybersecurity: direct link, hf CLI and curl.
- Browser
- Download file 432 Bytes
-
https://huggingface.co/pki/ner-cybersecurity/resolve/main/parser/cfg
- Command line
-
hf download hf://pki/ner-cybersecurity/parser/cfg
-
curl -L -o cfg https://huggingface.co/pki/ner-cybersecurity/resolve/main/parser/cfg
432 Bytes
| { | |
| "beam_width":1, | |
| "beam_density":0.0, | |
| "beam_update_prob":1.0, | |
| "cnn_maxout_pieces":3, | |
| "nr_feature_tokens":8, | |
| "deprecation_fixes":{ | |
| "vectors_name":null | |
| }, | |
| "learn_tokens":false, | |
| "nr_class":107, | |
| "hidden_depth":1, | |
| "token_vector_width":96, | |
| "hidden_width":64, | |
| "maxout_pieces":2, | |
| "pretrained_vectors":null, | |
| "bilstm_depth":0, | |
| "self_attn_depth":0, | |
| "conv_depth":4, | |
| "conv_window":1, | |
| "embed_size":2000 | |
| } |