Initial release: grc_dep_web_sm v3.8.0

.gitattributes

@@ -33,3 +33,10 @@ 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
+grc_dep_web_sm-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
+morphologizer/model filter=lfs diff=lfs merge=lfs -text
+parser/model filter=lfs diff=lfs merge=lfs -text
+senter/model filter=lfs diff=lfs merge=lfs -text
+tok2vec/model filter=lfs diff=lfs merge=lfs -text
+trainable_lemmatizer/model filter=lfs diff=lfs merge=lfs -text
+trainable_lemmatizer/trees filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,130 @@
+---
+tags:
+- spacy
+- token-classification
+language:
+- grc
+license: mit
+---
+---
+tags:
+- spacy
+- token-classification
+- ancient-greek
+language:
+- grc
+license: mit
+model-index:
+- name: grc_dep_web_sm
+  results:
+  - task:
+      name: POS Tagging
+      type: token-classification
+    metrics:
+    - name: POS Accuracy
+      type: accuracy
+      value: 0.9002
+    - name: TAG (XPOS) Accuracy
+      type: accuracy
+      value: 0.9004
+  - task:
+      name: Lemmatization
+      type: token-classification
+    metrics:
+    - name: Lemma Accuracy
+      type: accuracy
+      value: 0.9336
+  - task:
+      name: Dependency Parsing
+      type: token-classification
+    metrics:
+    - name: Labeled Attachment Score
+      type: f_score
+      value: 0.6420
+---
+
+# grc_dep_web_sm
+
+**Ancient Greek** multi-task CNN pipeline for [spaCy](https://spacy.io), part of the [LatinCy](https://huggingface.co/latincy) project.
+
+Small model without word vectors. Trained on Universal Dependencies Ancient Greek treebanks (AGLDT, PROIEL, Perseus) with a 1.2M-entry lookup lemmatizer overlay built from CLTK Morpheus, UD treebanks, and Wiktionary.
+
+| Feature | Description |
+| --- | --- |
+| **Name** | `grc_dep_web_sm` |
+| **Version** | `3.8.0` |
+| **spaCy** | `>=3.8.11,<3.9.0` |
+| **Default Pipeline** | `senter`, `tok2vec`, `tagger`, `morphologizer`, `trainable_lemmatizer`, `lookup_lemmatizer`, `parser` |
+| **Components** | `senter`, `tok2vec`, `tagger`, `morphologizer`, `trainable_lemmatizer`, `lookup_lemmatizer`, `parser` |
+| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
+| **License** | `MIT` |
+| **Author** | [Patrick J. Burns](https://huggingface.co/latincy) |
+
+## Install
+
+```bash
+pip install https://huggingface.co/latincy/grc_dep_web_sm/resolve/main/grc_dep_web_sm-3.8.0-py3-none-any.whl
+```
+
+## Usage
+
+```python
+import spacy
+
+nlp = spacy.load("grc_dep_web_sm")
+doc = nlp("μῆνιν ἄειδε θεὰ Πηληϊάδεω Ἀχιλῆος")
+
+for token in doc:
+    print(token.text, token.pos_, token.lemma_, token.dep_)
+# μῆνιν   NOUN  μῆνις    obj
+# ἄειδε   VERB  ἀείδω    ROOT
+# θεὰ     NOUN  θεά      nsubj
+# Πηληϊάδεω NOUN Πηλείδης nmod
+# Ἀχιλῆος NOUN  Ἀχιλῆος  nmod
+```
+
+## Evaluation
+
+Scores on held-out UD test data (combined AGLDT + PROIEL + Perseus).
+
+| Metric | Score |
+| --- | --- |
+| **POS (UPOS) Accuracy** | 90.02 |
+| **TAG (XPOS) Accuracy** | 90.04 |
+| **Morph (UFeats) Accuracy** | 78.38 |
+| **Lemma Accuracy** | 93.36 |
+| **Unlabeled Attachment Score (UAS)** | 73.33 |
+| **Labeled Attachment Score (LAS)** | 64.20 |
+| **Sentences F-Score** | 88.18 |
+
+## Training Data
+
+| Source | Description |
+| --- | --- |
+| [UD_Ancient_Greek-AGLDT](https://github.com/UniversalDependencies/UD_Ancient_Greek-AGLDT) | Ancient Greek Dependency Treebank |
+| [UD_Ancient_Greek-PROIEL](https://github.com/UniversalDependencies/UD_Ancient_Greek-PROIEL) | PROIEL Ancient Greek treebank |
+| [UD_Ancient_Greek-Perseus](https://github.com/UniversalDependencies/UD_Ancient_Greek-Perseus) | Perseus Ancient Greek treebank |
+
+## Components
+
+- **tok2vec** — Shared token-to-vector encoder (CNN, width 96)
+- **tagger** — Fine-grained POS tagger (XPOS)
+- **morphologizer** — Morphological feature assignment (UPOS + UFeats)
+- **trainable_lemmatizer** — Edit-tree lemmatizer
+- **lookup_lemmatizer** — 1.2M-entry dictionary lemmatizer overlay (CLTK Morpheus + UD + Wiktionary); normalizes grave accents to acute at query time
+- **parser** — Dependency parser (transition-based)
+- **senter** — Sentence segmenter
+
+## Label Scheme
+
+<details>
+
+<summary>View label scheme (1796 labels for 3 components)</summary>
+
+**`tagger`**: `adjective`, `adverb`, `conjunction`, `conjunction_adverb`, `conjunction_pronoun`, `determiner`, `interjection`, `noun`, `number`, `particle`, `preposition`, `pronoun`, `proper_noun`, `punc`, `unknown`, `verb`
+
+**`morphologizer`**: 1764 morphological feature combinations
+
+**`parser`**: `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `case`, `cc`, `ccomp`, `conj`, `cop`, `csubj`, `dep`, `det`, `discourse`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `orphan`, `parataxis`, `punct`, `vocative`, `xcomp`
+
+</details>

config.cfg

@@ -0,0 +1,239 @@
+[paths]
+stage1_model = "training/stage1/sm-v03/model-best"
+train = null
+dev = null
+vectors = null
+init_tok2vec = null
+
+[system]
+seed = 0
+gpu_allocator = null
+
+[nlp]
+lang = "grc"
+pipeline = ["senter","tok2vec","tagger","morphologizer","trainable_lemmatizer","lookup_lemmatizer","parser"]
+batch_size = 1000
+disabled = []
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+vectors = {"@vectors":"spacy.Vectors.v1"}
+
+[components]
+
+[components.lookup_lemmatizer]
+factory = "lookup_lemmatizer"
+
+[components.morphologizer]
+factory = "morphologizer"
+extend = false
+label_smoothing = 0.0
+overwrite = true
+scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
+
+[components.morphologizer.model]
+@architectures = "spacy.Tagger.v2"
+nO = null
+normalize = false
+
+[components.morphologizer.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = 96
+upstream = "tok2vec"
+
+[components.parser]
+factory = "parser"
+learn_tokens = false
+min_action_freq = 30
+moves = null
+scorer = {"@scorers":"spacy.parser_scorer.v1"}
+update_with_oracle_cut_size = 100
+
+[components.parser.model]
+@architectures = "spacy.TransitionBasedParser.v2"
+state_type = "parser"
+extra_state_tokens = false
+hidden_width = 128
+maxout_pieces = 3
+use_upper = true
+nO = null
+
+[components.parser.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = 96
+upstream = "tok2vec"
+
+[components.senter]
+factory = "senter"
+overwrite = false
+scorer = {"@scorers":"spacy.senter_scorer.v1"}
+
+[components.senter.model]
+@architectures = "spacy.Tagger.v2"
+nO = null
+normalize = false
+
+[components.senter.model.tok2vec]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.senter.model.tok2vec.embed]
+@architectures = "spacy.MultiHashEmbed.v2"
+width = 16
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
+rows = [1000,500,500,500]
+include_static_vectors = false
+
+[components.senter.model.tok2vec.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 16
+depth = 2
+window_size = 1
+maxout_pieces = 2
+
+[components.tagger]
+factory = "tagger"
+label_smoothing = 0.0
+neg_prefix = "!"
+overwrite = false
+scorer = {"@scorers":"spacy.tagger_scorer.v1"}
+
+[components.tagger.model]
+@architectures = "spacy.Tagger.v2"
+nO = null
+normalize = false
+
+[components.tagger.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = 96
+upstream = "tok2vec"
+
+[components.tok2vec]
+factory = "tok2vec"
+
+[components.tok2vec.model]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.tok2vec.model.embed]
+@architectures = "spacy.MultiHashEmbed.v1"
+width = 96
+attrs = ["LOWER","PREFIX","SUFFIX","SHAPE"]
+rows = [5000,1000,2500,2500]
+include_static_vectors = false
+
+[components.tok2vec.model.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 96
+depth = 4
+window_size = 1
+maxout_pieces = 3
+
+[components.trainable_lemmatizer]
+factory = "trainable_lemmatizer"
+backoff = "orth"
+min_tree_freq = 3
+overwrite = false
+scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
+top_k = 1
+
+[components.trainable_lemmatizer.model]
+@architectures = "spacy.Tagger.v2"
+nO = null
+normalize = false
+
+[components.trainable_lemmatizer.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = 96
+upstream = "tok2vec"
+
+[corpora]
+
+[corpora.dev]
+@readers = "spacy.Corpus.v1"
+path = ${paths.dev}
+gold_preproc = false
+max_length = 0
+limit = 0
+augmenter = null
+
+[corpora.train]
+@readers = "spacy.Corpus.v1"
+path = ${paths.train}
+gold_preproc = false
+max_length = 0
+limit = 0
+augmenter = null
+
+[training]
+seed = ${system.seed}
+gpu_allocator = ${system.gpu_allocator}
+dropout = 0.1
+accumulate_gradient = 1
+patience = 1600
+max_epochs = 0
+max_steps = 20000
+eval_frequency = 200
+frozen_components = []
+annotating_components = []
+dev_corpus = "corpora.dev"
+train_corpus = "corpora.train"
+before_to_disk = null
+before_update = null
+
+[training.batcher]
+@batchers = "spacy.batch_by_words.v1"
+discard_oversize = false
+tolerance = 0.2
+get_length = null
+
+[training.batcher.size]
+@schedules = "compounding.v1"
+start = 100
+stop = 1000
+compound = 1.001
+t = 0.0
+
+[training.logger]
+@loggers = "spacy.ConsoleLogger.v1"
+progress_bar = false
+
+[training.optimizer]
+@optimizers = "Adam.v1"
+beta1 = 0.9
+beta2 = 0.999
+L2_is_weight_decay = true
+L2 = 0.01
+grad_clip = 1.0
+use_averages = false
+eps = 0.00000001
+learn_rate = 0.001
+
+[training.score_weights]
+sents_f = 0.0
+sents_p = null
+sents_r = null
+tag_acc = 0.26
+pos_acc = 0.12
+tag_micro_p = null
+tag_micro_r = null
+tag_micro_f = null
+morph_acc = 0.12
+morph_per_feat = null
+lemma_acc = 0.26
+dep_uas = 0.12
+dep_las = 0.12
+dep_las_per_type = null
+
+[pretraining]
+
+[initialize]
+vectors = ${paths.vectors}
+init_tok2vec = ${paths.init_tok2vec}
+vocab_data = null
+lookups = null
+before_init = null
+after_init = null
+
+[initialize.components]
+
+[initialize.tokenizer]

grc_dep_web_sm-any-py3-none-any.whl

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+size 24892077

morphologizer/model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:92703809bb8d486504874d2cd083c7bbb69697de9ba47e23ddf8602dcd014b8c
+size 679054

package_functions.py

@@ -0,0 +1,128 @@
+# Packaging-ready functions for grc_core_web_sm
+#
+# This file is included in the wheel via `spacy package --code`.
+# It loads the lookup table from vocab.lookups (embedded in the model)
+# instead of from a filesystem path.
+
+from __future__ import annotations
+
+import string
+import unicodedata
+from typing import Dict
+
+from spacy.language import Language
+from spacy.tokens import Doc, Token
+
+
+# ----- Greek accent normalization (inline, no external dependency) ----- #
+
+# Grave (VARIA) → Acute (OXIA) mapping for polytonic Greek
+_GRAVE_TO_ACUTE: Dict[str, str] = {
+    # Alpha with breathing
+    "\u1F02": "\u1F04", "\u1F03": "\u1F05",
+    "\u1F0A": "\u1F0C", "\u1F0B": "\u1F0D",
+    # Epsilon
+    "\u1F12": "\u1F14", "\u1F13": "\u1F15",
+    "\u1F1A": "\u1F1C", "\u1F1B": "\u1F1D",
+    # Eta
+    "\u1F22": "\u1F24", "\u1F23": "\u1F25",
+    "\u1F2A": "\u1F2C", "\u1F2B": "\u1F2D",
+    # Iota
+    "\u1F32": "\u1F34", "\u1F33": "\u1F35",
+    "\u1F3A": "\u1F3C", "\u1F3B": "\u1F3D",
+    # Omicron
+    "\u1F42": "\u1F44", "\u1F43": "\u1F45",
+    "\u1F4A": "\u1F4C", "\u1F4B": "\u1F4D",
+    # Upsilon
+    "\u1F52": "\u1F54", "\u1F53": "\u1F55", "\u1F5B": "\u1F5D",
+    # Omega
+    "\u1F62": "\u1F64", "\u1F63": "\u1F65",
+    "\u1F6A": "\u1F6C", "\u1F6B": "\u1F6D",
+    # Simple vowel + varia
+    "\u1F70": "\u1F71", "\u1F72": "\u1F73", "\u1F74": "\u1F75",
+    "\u1F76": "\u1F77", "\u1F78": "\u1F79", "\u1F7A": "\u1F7B",
+    "\u1F7C": "\u1F7D",
+    # With iota subscript
+    "\u1F82": "\u1F84", "\u1F83": "\u1F85",
+    "\u1F8A": "\u1F8C", "\u1F8B": "\u1F8D",
+    "\u1F92": "\u1F94", "\u1F93": "\u1F95",
+    "\u1F9A": "\u1F9C", "\u1F9B": "\u1F9D",
+    "\u1FA2": "\u1FA4", "\u1FA3": "\u1FA5",
+    "\u1FAA": "\u1FAC", "\u1FAB": "\u1FAD",
+    "\u1FB2": "\u1FB4", "\u1FC2": "\u1FC4", "\u1FF2": "\u1FF4",
+    # Capitals
+    "\u1FBA": "\u1FBB", "\u1FC8": "\u1FC9", "\u1FCA": "\u1FCB",
+    "\u1FDA": "\u1FDB", "\u1FEA": "\u1FEB", "\u1FF8": "\u1FF9",
+    "\u1FFA": "\u1FFB",
+    # Dialytika + varia
+    "\u1FD2": "\u1FD3", "\u1FE2": "\u1FE3",
+}
+
+_GRAVE_TO_ACUTE_TABLE = str.maketrans(_GRAVE_TO_ACUTE)
+
+
+def _normalize_greek(text: str) -> str:
+    """Normalize Greek text for lookup: grave→acute, strip macron/breve, NFC."""
+    if not text:
+        return text
+    # Strip macrons/breves (NFD → remove U+0304/U+0306 → NFC)
+    decomposed = unicodedata.normalize("NFD", text)
+    stripped = decomposed.replace("\u0304", "").replace("\u0306", "")
+    result = unicodedata.normalize("NFC", stripped)
+    # Grave → acute (precomposed)
+    result = result.translate(_GRAVE_TO_ACUTE_TABLE)
+    # Combining grave → acute
+    if "\u0300" in result:
+        result = result.replace("\u0300", "\u0301")
+    # Final NFC
+    return unicodedata.normalize("NFC", result)
+
+
+# ----- lookup_lemmatizer (loads from vocab.lookups) ----- #
+
+if not Token.has_extension("predicted_lemma"):
+    Token.set_extension("predicted_lemma", default=None)
+
+
+@Language.component(name="lookup_lemmatizer")
+def lookup_lemmatizer(doc: Doc) -> Doc:
+    """Lookup-based lemmatizer for Ancient Greek.
+
+    Assigns lemmas using a 1.2M-entry dictionary built from CLTK Morpheus,
+    UD treebanks, and Wiktionary. Normalizes grave→acute accents at query
+    time so running-text forms match citation entries.
+
+    Runs after trainable_lemmatizer: overrides only when a lookup match
+    exists, preserving the trainable model's output for unseen forms.
+
+    In this packaging-ready version, lookups are loaded from the model's
+    vocab.lookups (embedded in vocab/lookups.bin) rather than a filesystem path.
+    """
+    lookups = doc.vocab.lookups
+    if not lookups.has_table("lemma_lookup"):
+        return doc
+    table = lookups.get_table("lemma_lookup")
+
+    for token in doc:
+        # Store trainable lemmatizer's prediction
+        token._.predicted_lemma = token.lemma_
+
+        # Skip punctuation
+        if token.pos_ == "PUNCT" or token.text in string.punctuation:
+            continue
+
+        # Normalize for lookup (grave→acute, strip macron/breve)
+        normalized = _normalize_greek(token.text)
+
+        # Direct match
+        if normalized in table:
+            token.lemma_ = table[normalized]
+            continue
+
+        # Case-insensitive fallback for capitalized words
+        if normalized and normalized[0].isupper():
+            lower = normalized.lower()
+            if lower in table:
+                token.lemma_ = table[lower]
+
+    return doc

parser/cfg

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+{
+  "moves":null,
+  "update_with_oracle_cut_size":100,
+  "multitasks":[
+
+  ],
+  "min_action_freq":30,
+  "learn_tokens":false,
+  "beam_width":1,
+  "beam_density":0.0,
+  "beam_update_prob":0.0,
+  "incorrect_spans_key":null
+}

parser/model

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+size 1726918

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senter/cfg

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+{
+  "overwrite":false
+}

senter/model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a2e46e289fbb1eb9290116498916082be7a5d4c5810821ca4de017dc57a71905
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tagger/cfg

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+{
+  "label_smoothing":0.0,
+  "labels":[
+    "adjective",
+    "adverb",
+    "conjunction",
+    "conjunction_adverb",
+    "conjunction_pronoun",
+    "determiner",
+    "interjection",
+    "noun",
+    "number",
+    "particle",
+    "preposition",
+    "pronoun",
+    "proper_noun",
+    "punc",
+    "unknown",
+    "verb"
+  ],
+  "neg_prefix":"!",
+  "overwrite":false
+}

tok2vec/cfg

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+{
+
+}

tok2vec/model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8a41c2481b08d9c777b8dc45ffa85860d9bc71ec1e67159fd48557dae80a9102
+size 6009092

tokenizer

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vocab/key2row

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vocab/lookups.bin

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vocab/vectors.cfg

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