initial upload

.gitattributes

@@ -33,3 +33,9 @@ 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
+lv_roberta_large-1.0.0-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
+tagger/model filter=lfs diff=lfs merge=lfs -text
+transformer/model filter=lfs diff=lfs merge=lfs -text

LICENSE

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LICENSES_SOURCES

@@ -0,0 +1,34 @@
+This model was trained using the Universal Dependencies Latvian Treebank (UD_Latvian-LVTB).
+
+Repository: https://github.com/UniversalDependencies/UD_Latvian-LVTB
+Version: v2.16 (released 2025-05-15)
+
+License:
+  Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
+  https://creativecommons.org/licenses/by-sa/4.0/
+
+Acknowledgments:
+  Latvian UD Treebank is based on the Latvian Treebank (LVTB), created at the 
+  University of Latvia, Institute of Mathematics and Computer Science, Artificial Intelligence Laboratory.
+
+  Contributors include:
+    - Lauma Pretkalniņa
+    - Laura Rituma
+    - Gunta Nešpore-Bērzkalne
+    - Baiba Saulīte
+    - Artūrs Znotiņš
+    - Normunds Grūzītis
+    - and others (see repository for full list)
+
+Funding acknowledgments:
+  Supported by European Regional Development Fund under the grant agreement 
+  No. 1.1.1.1/16/A/219, in synergy with grant agreement No. 1.1.1.2/VIAA/1/16/188.
+  Also supported by State Research Programmes "National Identity", "Digital Resources for the Humanities" 
+  (VPP-IZM-DH-2020/1-0001), and "Research on Modern Latvian Language and Development of Language Technology" 
+  (VPP-LETONIKA-2021/1-0006).
+
+Usage notes:
+  By using this model, you acknowledge that it was trained on data licensed 
+  under CC BY-SA 4.0. You must comply with the terms of that license when using 
+  this model, including providing appropriate attribution and ShareAlike for 
+  derivative works.

README.md

@@ -0,0 +1,220 @@
+---
+language:
+- lv
+base_model:
+- FacebookAI/xlm-roberta-large
+license: cc-by-sa-4.0
+datasets:
+- universal_dependencies
+metrics:
+- accuracy
+- uas
+- las
+---
+
+# Latvian SpaCy Model: lv_roberta_large
+
+## Hugging Face Model Repo:
+https://huggingface.co/JesseHuang922/lv_roberta_large
+
+---
+
+## Overview
+
+This is a **spaCy transformer-based pipeline for Latvian**, built with the **XLM-RoBERTa-large backbone**.  
+
+It includes the following components:  
+
+- **Transformer** (XLM-RoBERTa-large)
+- **Tagger**
+- **Morphologizer**
+- **Parser**
+- **Sentence Segmenter (senter)**
+- **Lemmatizer**
+- (Note: Transformer component internally uses a `tok2vec` listener)
+
+**Model type:** Transformer pipeline (XLM-RoBERTa-large backbone)  
+**Language:** Latvian (lv)  
+**Recommended hardware:** CPU for small-scale use, GPU recommended for faster inference.  
+
+---
+
+## Training Data
+
+The model was trained on the **Latvian UD Treebank v2.16**, which is derived from the **Latvian Treebank (LVTB)** created at the University of Latvia, Institute of Mathematics and Computer Science, Artificial Intelligence Laboratory (AI Lab).  
+
+- **Dataset source:** [UD Latvian LVTB](https://github.com/UniversalDependencies/UD_Latvian-LVTB)  
+- **License:** [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)  
+- **Data splits:**  
+  - Train: 15,055 sentences  
+  - Dev: 2,080 sentences  
+  - Test: 2,396 sentences  
+
+---
+
+## Acknowledgements
+
+- Thanks to the **University of Latvia, AI Lab**, and all contributors of the **Latvian UD Treebank**.  
+- Model development supported by [LazyBomb.SIA].  
+- Inspired by the **spaCy ecosystem** and training framework.  
+- The Latvian UD Treebank was developed with support from multiple grants, including:  
+  - European Regional Development Fund (Grant No. 1.1.1.1/16/A/219, 1.1.1.2/VIAA/1/16/188)  
+  - State Research Programme "National Identity"  
+  - State Research Programme "Digital Resources for the Humanities" (Grant No. VPP-IZM-DH-2020/1-0001)  
+  - State Research Programme "Research on Modern Latvian Language and Development of Language Technology" (Grant No. VPP-LETONIKA-2021/1-0006)  
+
+---
+
+## Special Thanks
+Special Thanks to all contributors who participated in the Beta test and espically those who provided valuable feedback
+
+**The list is waiting**
+
+---
+
+## License
+
+This model is released under the [Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/).
+
+You are free to:
+- **Share** — copy and redistribute the material in any medium or format, for any purpose, even commercially.  
+- **Adapt** — remix, transform, and build upon the material for any purpose, even commercially.  
+
+Under the following terms:
+- **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made.  
+- **ShareAlike** — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.  
+
+---
+
+## References
+
+- Pretkalniņa, L., Rituma, L., Saulīte, B., et al. (2016–2025). Universal Dependencies Latvian Treebank (LVTB).  
+- Grūzītis, N., Znotiņš, A., Nešpore-Bērzkalne, G., Paikens, P., et al. (2018). Creation of a Balanced State-of-the-Art Multilayer Corpus for NLU. *LREC 2018*.  
+- Pretkalniņa, L., Rituma, L., Saulīte, B. (2016). Universal Dependency Treebank for Latvian: A Pilot. *Baltic Perspective Workshop*.  
+
+---
+
+---
+
+## Usage
+You can either:
+
+1. **Download the model directly from the Hugging Face Hub**  
+   Using `huggingface_hub.snapshot_download`, the model files will be automatically fetched and cached locally.
+
+      ```python
+      import spacy
+      from huggingface_hub import snapshot_download
+      
+      # Load the pipeline
+      model_dir = snapshot_download(repo_id="JesseHuang922/lv_roberta_large", repo_type="model")
+      nlp = spacy.load(model_dir)
+      ```
+
+2. **Install from the pre-built wheel package**  
+   Download the wheel file (**lv_roberta_large-1.0.0-py3-none-any.whl**) and install it into your virtual environment with:
+
+       ```bash
+       pip install lv_roberta_large-1.0.0-py3-none-any.whl
+       
+---
+
+## Dependencies
+
+The following Python packages are required to run the Latvian XLM-RoBERTa spaCy pipeline:
+
+| Package                | Minimum Version | Notes                                                                                  | 
+| ---------------------- | --------------- | -------------------------------------------------------------------------------------- | 
+| **spaCy**              | 3.8.7           | Main NLP framework                                                          | 
+| **spacy-transformers** | 1.3.9           | Integrates spaCy with Hugging Face Transformers  | 
+| **transformers**       | 4.49.0          | Hugging Face Transformers library                       | 
+| **torch**              | 2.8.0           | PyTorch backend for transformers                           | 
+| **tokenizers**         | 0.21.4          | Fast tokenizer support                                                        | 
+| **safetensors**        | 0.6.2           | Secure tensor storage for transformer weights                      | 
+| **huggingface-hub**    | 0.34.4          | Download and manage the model files from the Hugging Face Hub      |
+
+## Optional but recommended 
+| Package                | Minimum Version | Notes                                                                                  | 
+| ---------------------- | --------------- | -------------------------------------------------------------------------------------- | 
+| **hf-xet**             | 1.1.10          | if you need to download or upload large files from the Hugging Face Hub and use the Xet storage backend     |
+
+## Install all dependencies with just one command line:
+```bash
+pip install \
+spacy>=3.8.7 \
+spacy-transformers>=1.3.9 \
+transformers>=4.49.0 \
+torch>=2.8.0 \
+tokenizers>=0.21.4 \
+safetensors>=0.6.2 \
+huggingface-hub>=0.34.4 \
+hf-xet>=1.1.10
+```
+
+## Example Code
+
+```python
+import spacy
+import numpy as np
+from huggingface_hub import snapshot_download
+
+# Load the pipeline
+model_dir = snapshot_download(repo_id="JesseHuang922/lv_roberta_large", repo_type="model")
+nlp = spacy.load(model_dir)
+
+# Example text
+text = """Baltijas jūras nosaukums ir devis nosaukumu baltu valodām un Baltijas valstīm.
+Terminu "Baltijas jūra" (Mare Balticum) pirmoreiz lietoja vācu hronists Brēmenes Ādams 11. gadsimtā."""
+
+# Process text
+doc = nlp(text)
+
+# ------------------------
+# Tokenization 
+# ------------------------
+print("Tokens:")
+print([token.text for token in doc])
+
+# ------------------------
+# Lemmatization
+# ------------------------
+print("Lemmas:")
+print([token.lemma_ for token in doc])
+
+# ------------------------
+# Part-of-Speech Tagging
+# ------------------------
+print("POS tags:")
+for token in doc:
+    print(f"{token.text}: {token.pos_} ({token.tag_})")
+
+# ------------------------
+# Morphological Features
+# ------------------------
+print("Morphological features:")
+for token in doc:
+    print(f"{token.text}: {token.morph}")
+
+# ------------------------
+# Dependency Parsing
+# ------------------------
+print("Dependency parsing:")
+for token in doc:
+    print(f"{token.text} <--{token.dep_}-- {token.head.text}")
+
+# ------------------------
+# Sentence Segmentation
+# ------------------------
+print("Sentences:")
+for sent in doc.sents:
+    print(sent.text)
+
+# ------------------------
+# Check Pipeline Components
+# ------------------------
+print("Pipeline components:")
+print(nlp.pipe_names)
+
+# Transformer vectors
+vectors = np.vstack([token.vector for token in doc])
+print("Token vectors shape:", vectors.shape)

config.cfg

@@ -0,0 +1,230 @@
+[paths]
+train = "./corpus/lv_lvtb-ud-train.spacy"
+dev = "./corpus/lv_lvtb-ud-dev.spacy"
+vectors = null
+init_tok2vec = null
+
+[system]
+gpu_allocator = "pytorch"
+seed = 0
+
+[nlp]
+lang = "lv"
+pipeline = ["transformer","trf_tok2vec","tagger","morphologizer","parser","senter","lemmatizer"]
+batch_size = 128
+disabled = []
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+vectors = {"@vectors":"spacy.Vectors.v1"}
+
+[components]
+
+[components.lemmatizer]
+factory = "lemmatizer"
+mode = "lookup"
+model = null
+overwrite = false
+scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
+
+[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-transformers.TransformerListener.v1"
+grad_factor = 1.0
+pooling = {"@layers":"reduce_mean.v1"}
+upstream = "*"
+
+[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 = false
+nO = null
+
+[components.parser.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+pooling = {"@layers":"reduce_mean.v1"}
+upstream = "*"
+
+[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.HashEmbedCNN.v2"
+pretrained_vectors = null
+width = 12
+depth = 1
+embed_size = 2000
+window_size = 1
+maxout_pieces = 2
+subword_features = true
+
+[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-transformers.TransformerListener.v1"
+grad_factor = 1.0
+pooling = {"@layers":"reduce_mean.v1"}
+upstream = "*"
+
+[components.transformer]
+factory = "transformer"
+max_batch_items = 4096
+set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
+
+[components.transformer.model]
+@architectures = "spacy-transformers.TransformerModel.v3"
+name = "xlm-roberta-large"
+mixed_precision = true
+
+[components.transformer.model.get_spans]
+@span_getters = "spacy-transformers.strided_spans.v1"
+window = 128
+stride = 96
+
+[components.transformer.model.grad_scaler_config]
+
+[components.transformer.model.tokenizer_config]
+use_fast = true
+
+[components.transformer.model.transformer_config]
+
+[components.trf_tok2vec]
+factory = "tok2vec"
+
+[components.trf_tok2vec.model]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+pooling = {"@layers":"reduce_mean.v1"}
+upstream = "*"
+
+[corpora]
+
+[corpora.dev]
+@readers = "spacy.Corpus.v1"
+path = ${paths.dev}
+max_length = 0
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[corpora.train]
+@readers = "spacy.Corpus.v1"
+path = ${paths.train}
+max_length = 0
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[training]
+accumulate_gradient = 3
+dev_corpus = "corpora.dev"
+train_corpus = "corpora.train"
+seed = ${system.seed}
+gpu_allocator = ${system.gpu_allocator}
+dropout = 0.1
+patience = 1600
+max_epochs = 0
+max_steps = 20000
+eval_frequency = 200
+frozen_components = []
+annotating_components = []
+before_to_disk = null
+before_update = null
+
+[training.batcher]
+@batchers = "spacy.batch_by_padded.v1"
+discard_oversize = true
+size = 2000
+buffer = 256
+get_length = null
+
+[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
+
+[training.optimizer.learn_rate]
+@schedules = "warmup_linear.v1"
+warmup_steps = 250
+total_steps = 20000
+initial_rate = 0.00005
+
+[training.score_weights]
+tag_acc = 0.13
+pos_acc = 0.06
+tag_micro_p = null
+tag_micro_r = null
+tag_micro_f = null
+morph_acc = 0.06
+morph_per_feat = null
+dep_uas = 0.06
+dep_las = 0.06
+dep_las_per_type = null
+sents_p = 0.0
+sents_r = 0.0
+sents_f = 0.13
+lemma_acc = 0.5
+
+[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]

lemmatizer/lookups/lookups.bin

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+oid sha256:fdf57678281c5d7d357daecd8ac23dcdf387732024435ff2a36dd9a3ae236b4a
+size 1008253

lv_roberta_large-1.0.0-py3-none-any.whl

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morphologizer/model

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+oid sha256:7655e4e05a1ee5eee2a06ce50746910cd0f6c19aa9a49504a759b9451c3ccd8d
+size 4563953

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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parser/moves

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senter/cfg

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+  "overwrite":false
+}

senter/model

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tagger/cfg

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+  "overwrite":false
+}

tagger/model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:843733ef06620bed21d6954f93846e6288d04ff0841d852199ae6479f5b60cdb
+size 7479053

tokenizer

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