Token Classification
Transformers
Safetensors
Ancient Greek (to 1453)
char_bert_joint
ancient-greek
classical-philology
character-level
masked-diffusion
dependency-parsing
pos-tagging
lemmatization
custom_code
Instructions to use Ericu950/Stoicheia-tagger-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ericu950/Stoicheia-tagger-parser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Ericu950/Stoicheia-tagger-parser", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Ericu950/Stoicheia-tagger-parser", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 841 Bytes
cd8ae16 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | {
"n_alpha": 24,
"mask_id": 24,
"blank_id": 25,
"pad_id": 26,
"n_char_ids": 27,
"n_boundary": 4,
"n_dia": 49,
"n_punct": 7,
"d_model": 1024,
"n_heads": 16,
"depth": 32,
"char_window": 256,
"attn_impl": "sdpa",
"qk_norm": true,
"use_cap": true,
"pool": "mean",
"head_dropout": 0.33,
"scalar_mix": true,
"xpos_len": 9,
"n_xpos_classes": [
14,
4,
4,
8,
8,
5,
5,
6,
3
],
"n_script": 18839,
"n_upos": 13,
"use_flat": true,
"n_flat_tags": 1222,
"d_arc": 500,
"d_rel": 150,
"n_labels": 24,
"parse_dropout": 0.33,
"max_chars": 2048,
"max_words": 384,
"model_type": "char_bert_joint",
"auto_map": {
"AutoConfig": "configuration_char_bert_joint.CharBertJointConfig",
"AutoModel": "modeling_char_bert_joint.CharBertForTaggingAndParsing"
}
} |