Update spaCy pipeline
Browse files- .gitattributes +3 -0
- README.md +97 -0
- attribute_ruler/patterns +0 -0
- config.cfg +257 -0
- meta.json +507 -0
- ner/cfg +13 -0
- ner/model +0 -0
- ner/moves +1 -0
- parser/cfg +13 -0
- parser/model +0 -0
- parser/moves +1 -0
- tagger/cfg +43 -0
- tagger/model +0 -0
- tokenizer/cfg +3 -0
- tokenizer/pkuseg_model/features.msgpack +3 -0
- tokenizer/pkuseg_model/weights.npz +3 -0
- tokenizer/pkuseg_processors +3 -0
- transformer/cfg +3 -0
- transformer/model +3 -0
- vocab/key2row +1 -0
- vocab/lookups.bin +3 -0
- vocab/strings.json +0 -0
- vocab/vectors +0 -0
- vocab/vectors.cfg +3 -0
- zh_core_web_trf-any-py3-none-any.whl +3 -0
.gitattributes
CHANGED
@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer/pkuseg_processors filter=lfs diff=lfs merge=lfs -text
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transformer/model filter=lfs diff=lfs merge=lfs -text
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zh_core_web_trf-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
@@ -0,0 +1,97 @@
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---
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tags:
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- spacy
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- token-classification
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language:
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- zh
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license: mit
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model-index:
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- name: zh_core_web_trf
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results:
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- task:
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name: NER
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type: token-classification
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metrics:
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- name: NER Precision
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type: precision
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value: 0.7608897127
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- name: NER Recall
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type: recall
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value: 0.7217582418
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- name: NER F Score
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type: f_score
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value: 0.7408075795
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- task:
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name: TAG
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type: token-classification
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metrics:
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- name: TAG (XPOS) Accuracy
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type: accuracy
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value: 0.9175332527
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- task:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Unlabeled Attachment Score (UAS)
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type: f_score
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value: 0.7572203056
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- task:
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name: LABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Labeled Attachment Score (LAS)
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type: f_score
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value: 0.7145288854
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- task:
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name: SENTS
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type: token-classification
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metrics:
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- name: Sentences F-Score
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type: f_score
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value: 0.6920716113
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---
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Chinese transformer pipeline (Transformer(name='bert-base-chinese', piece_encoder='bert-wordpiece', stride=152, type='bert', width=768, window=208, vocab_size=21128)). Components: transformer, tagger, parser, ner, attribute_ruler.
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| Feature | Description |
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| --- | --- |
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| **Name** | `zh_core_web_trf` |
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| **Version** | `3.7.2` |
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| **spaCy** | `>=3.7.0,<3.8.0` |
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| **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
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| **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `ner` |
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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| **Sources** | [OntoNotes 5](https://catalog.ldc.upenn.edu/LDC2013T19) (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br>[CoreNLP Universal Dependencies Converter](https://nlp.stanford.edu/software/stanford-dependencies.html) (Stanford NLP Group)<br>[bert-base-chinese](https://huggingface.co/bert-base-chinese) (Hugging Face) |
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| **License** | `MIT` |
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| **Author** | [Explosion](https://explosion.ai) |
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### Label Scheme
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<details>
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<summary>View label scheme (99 labels for 3 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`tagger`** | `AD`, `AS`, `BA`, `CC`, `CD`, `CS`, `DEC`, `DEG`, `DER`, `DEV`, `DT`, `ETC`, `FW`, `IJ`, `INF`, `JJ`, `LB`, `LC`, `M`, `MSP`, `NN`, `NR`, `NT`, `OD`, `ON`, `P`, `PN`, `PU`, `SB`, `SP`, `URL`, `VA`, `VC`, `VE`, `VV`, `X` |
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| **`parser`** | `ROOT`, `acl`, `advcl:loc`, `advmod`, `advmod:dvp`, `advmod:loc`, `advmod:rcomp`, `amod`, `amod:ordmod`, `appos`, `aux:asp`, `aux:ba`, `aux:modal`, `aux:prtmod`, `auxpass`, `case`, `cc`, `ccomp`, `compound:nn`, `compound:vc`, `conj`, `cop`, `dep`, `det`, `discourse`, `dobj`, `etc`, `mark`, `mark:clf`, `name`, `neg`, `nmod`, `nmod:assmod`, `nmod:poss`, `nmod:prep`, `nmod:range`, `nmod:tmod`, `nmod:topic`, `nsubj`, `nsubj:xsubj`, `nsubjpass`, `nummod`, `parataxis:prnmod`, `punct`, `xcomp` |
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
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</details>
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### Accuracy
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| Type | Score |
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| --- | --- |
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| `TOKEN_ACC` | 95.85 |
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| `TOKEN_P` | 94.58 |
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| `TOKEN_R` | 91.36 |
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| `TOKEN_F` | 92.94 |
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| `TAG_ACC` | 91.75 |
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| `SENTS_P` | 70.92 |
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| `SENTS_R` | 67.57 |
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| `SENTS_F` | 69.21 |
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| `DEP_UAS` | 75.72 |
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| `DEP_LAS` | 71.45 |
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| `ENTS_P` | 76.09 |
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| `ENTS_R` | 72.18 |
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| `ENTS_F` | 74.08 |
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attribute_ruler/patterns
ADDED
Binary file (2.12 kB). View file
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config.cfg
ADDED
@@ -0,0 +1,257 @@
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[paths]
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train = null
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dev = null
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vectors = null
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init_tok2vec = null
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[system]
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gpu_allocator = "pytorch"
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seed = 1
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[nlp]
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lang = "zh"
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pipeline = ["transformer","tagger","parser","attribute_ruler","ner"]
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disabled = []
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before_creation = null
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after_creation = null
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after_pipeline_creation = null
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batch_size = 64
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vectors = {"@vectors":"spacy.Vectors.v1"}
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[nlp.tokenizer]
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@tokenizers = "spacy.zh.ChineseTokenizer"
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segmenter = "pkuseg"
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[components]
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[components.attribute_ruler]
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factory = "attribute_ruler"
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scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
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validate = false
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[components.ner]
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factory = "ner"
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incorrect_spans_key = null
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moves = null
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scorer = {"@scorers":"spacy.ner_scorer.v1"}
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update_with_oracle_cut_size = 100
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[components.ner.model]
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@architectures = "spacy.TransitionBasedParser.v2"
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state_type = "ner"
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extra_state_tokens = false
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hidden_width = 64
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maxout_pieces = 2
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use_upper = false
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nO = null
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[components.ner.model.tok2vec]
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@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
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width = ${components.transformer.model.hidden_width}
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upstream = "transformer"
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pooling = {"@layers":"reduce_mean.v1"}
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grad_factor = 1.0
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[components.parser]
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factory = "parser"
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learn_tokens = false
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min_action_freq = 30
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moves = null
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scorer = {"@scorers":"spacy.parser_scorer.v1"}
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update_with_oracle_cut_size = 100
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[components.parser.model]
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@architectures = "spacy.TransitionBasedParser.v2"
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state_type = "parser"
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extra_state_tokens = false
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hidden_width = 64
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maxout_pieces = 2
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use_upper = false
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nO = null
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[components.parser.model.tok2vec]
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@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
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width = ${components.transformer.model.hidden_width}
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upstream = "transformer"
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pooling = {"@layers":"reduce_mean.v1"}
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grad_factor = 1.0
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[components.tagger]
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factory = "tagger"
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label_smoothing = 0.0
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neg_prefix = "!"
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overwrite = false
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scorer = {"@scorers":"spacy.tagger_scorer.v1"}
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[components.tagger.model]
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@architectures = "spacy.Tagger.v2"
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nO = null
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normalize = false
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[components.tagger.model.tok2vec]
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@architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
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width = ${components.transformer.model.hidden_width}
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upstream = "transformer"
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pooling = {"@layers":"reduce_mean.v1"}
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grad_factor = 1.0
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[components.transformer]
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factory = "curated_transformer"
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all_layer_outputs = false
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frozen = false
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[components.transformer.model]
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@architectures = "spacy-curated-transformers.BertTransformer.v1"
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vocab_size = 21128
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hidden_width = 768
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piece_encoder = {"@architectures":"spacy-curated-transformers.BertWordpieceEncoder.v1"}
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attention_probs_dropout_prob = 0.1
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hidden_act = "gelu"
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hidden_dropout_prob = 0.1
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intermediate_width = 3072
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layer_norm_eps = 0.0
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113 |
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max_position_embeddings = 512
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114 |
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model_max_length = 512
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115 |
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num_attention_heads = 12
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116 |
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num_hidden_layers = 12
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padding_idx = 0
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type_vocab_size = 2
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119 |
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torchscript = false
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120 |
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mixed_precision = false
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121 |
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wrapped_listener = null
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122 |
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[components.transformer.model.grad_scaler_config]
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124 |
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[components.transformer.model.with_spans]
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@architectures = "spacy-curated-transformers.WithStridedSpans.v1"
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stride = 152
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window = 208
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129 |
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batch_size = 384
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130 |
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[corpora]
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+
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[corpora.dev]
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134 |
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@readers = "spacy.Corpus.v1"
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135 |
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path = ${paths.dev}
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136 |
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gold_preproc = false
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137 |
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max_length = 0
|
138 |
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limit = 0
|
139 |
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augmenter = null
|
140 |
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|
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[corpora.train]
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@readers = "spacy.Corpus.v1"
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path = ${paths.train}
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144 |
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gold_preproc = false
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145 |
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max_length = 0
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146 |
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limit = 0
|
147 |
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augmenter = null
|
148 |
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|
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[training]
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train_corpus = "corpora.train"
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151 |
+
dev_corpus = "corpora.dev"
|
152 |
+
seed = ${system:seed}
|
153 |
+
gpu_allocator = ${system:gpu_allocator}
|
154 |
+
dropout = 0.1
|
155 |
+
accumulate_gradient = 3
|
156 |
+
patience = 5000
|
157 |
+
max_epochs = 0
|
158 |
+
max_steps = 20000
|
159 |
+
eval_frequency = 1000
|
160 |
+
frozen_components = []
|
161 |
+
before_to_disk = null
|
162 |
+
annotating_components = []
|
163 |
+
before_update = null
|
164 |
+
|
165 |
+
[training.batcher]
|
166 |
+
@batchers = "spacy.batch_by_words.v1"
|
167 |
+
discard_oversize = false
|
168 |
+
size = 2000
|
169 |
+
tolerance = 0.2
|
170 |
+
get_length = null
|
171 |
+
|
172 |
+
[training.logger]
|
173 |
+
@loggers = "spacy.ConsoleLogger.v1"
|
174 |
+
progress_bar = false
|
175 |
+
|
176 |
+
[training.optimizer]
|
177 |
+
@optimizers = "Adam.v1"
|
178 |
+
beta1 = 0.9
|
179 |
+
beta2 = 0.999
|
180 |
+
L2_is_weight_decay = true
|
181 |
+
L2 = 0.01
|
182 |
+
grad_clip = 1.0
|
183 |
+
use_averages = true
|
184 |
+
eps = 0.00000001
|
185 |
+
|
186 |
+
[training.optimizer.learn_rate]
|
187 |
+
@schedules = "warmup_linear.v1"
|
188 |
+
warmup_steps = 250
|
189 |
+
total_steps = 20000
|
190 |
+
initial_rate = 0.00005
|
191 |
+
|
192 |
+
[training.score_weights]
|
193 |
+
tag_acc = 0.32
|
194 |
+
dep_uas = 0.0
|
195 |
+
dep_las = 0.32
|
196 |
+
dep_las_per_type = null
|
197 |
+
sents_p = null
|
198 |
+
sents_r = null
|
199 |
+
sents_f = 0.04
|
200 |
+
ents_f = 0.32
|
201 |
+
ents_p = 0.0
|
202 |
+
ents_r = 0.0
|
203 |
+
ents_per_type = null
|
204 |
+
speed = 0.0
|
205 |
+
|
206 |
+
[pretraining]
|
207 |
+
|
208 |
+
[initialize]
|
209 |
+
vocab_data = null
|
210 |
+
vectors = ${paths.vectors}
|
211 |
+
init_tok2vec = ${paths.init_tok2vec}
|
212 |
+
before_init = null
|
213 |
+
after_init = null
|
214 |
+
|
215 |
+
[initialize.components]
|
216 |
+
|
217 |
+
[initialize.components.ner]
|
218 |
+
|
219 |
+
[initialize.components.ner.labels]
|
220 |
+
@readers = "spacy.read_labels.v1"
|
221 |
+
path = "corpus/labels/ner.json"
|
222 |
+
require = false
|
223 |
+
|
224 |
+
[initialize.components.parser]
|
225 |
+
|
226 |
+
[initialize.components.parser.labels]
|
227 |
+
@readers = "spacy.read_labels.v1"
|
228 |
+
path = "corpus/labels/parser.json"
|
229 |
+
require = false
|
230 |
+
|
231 |
+
[initialize.components.tagger]
|
232 |
+
|
233 |
+
[initialize.components.tagger.labels]
|
234 |
+
@readers = "spacy.read_labels.v1"
|
235 |
+
path = "corpus/labels/tagger.json"
|
236 |
+
require = false
|
237 |
+
|
238 |
+
[initialize.components.transformer]
|
239 |
+
|
240 |
+
[initialize.components.transformer.encoder_loader]
|
241 |
+
@model_loaders = "spacy-curated-transformers.HFTransformerEncoderLoader.v1"
|
242 |
+
name = "bert-base-chinese"
|
243 |
+
revision = "main"
|
244 |
+
|
245 |
+
[initialize.components.transformer.piecer_loader]
|
246 |
+
@model_loaders = "spacy-curated-transformers.HFPieceEncoderLoader.v1"
|
247 |
+
name = "bert-base-chinese"
|
248 |
+
revision = "main"
|
249 |
+
|
250 |
+
[initialize.lookups]
|
251 |
+
@misc = "spacy.LookupsDataLoader.v1"
|
252 |
+
lang = ${nlp.lang}
|
253 |
+
tables = []
|
254 |
+
|
255 |
+
[initialize.tokenizer]
|
256 |
+
pkuseg_model = "assets/pkuseg_model"
|
257 |
+
pkuseg_user_dict = "default"
|
meta.json
ADDED
@@ -0,0 +1,507 @@
|
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|
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|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"lang":"zh",
|
3 |
+
"name":"core_web_trf",
|
4 |
+
"version":"3.7.2",
|
5 |
+
"description":"Chinese transformer pipeline (Transformer(name='bert-base-chinese', piece_encoder='bert-wordpiece', stride=152, type='bert', width=768, window=208, vocab_size=21128)). Components: transformer, tagger, parser, ner, attribute_ruler.",
|
6 |
+
"author":"Explosion",
|
7 |
+
"email":"contact@explosion.ai",
|
8 |
+
"url":"https://explosion.ai",
|
9 |
+
"license":"MIT",
|
10 |
+
"spacy_version":">=3.7.0,<3.8.0",
|
11 |
+
"spacy_git_version":"4ec41e98f",
|
12 |
+
"vectors":{
|
13 |
+
"width":0,
|
14 |
+
"vectors":0,
|
15 |
+
"keys":0,
|
16 |
+
"name":null
|
17 |
+
},
|
18 |
+
"labels":{
|
19 |
+
"transformer":[
|
20 |
+
|
21 |
+
],
|
22 |
+
"tagger":[
|
23 |
+
"AD",
|
24 |
+
"AS",
|
25 |
+
"BA",
|
26 |
+
"CC",
|
27 |
+
"CD",
|
28 |
+
"CS",
|
29 |
+
"DEC",
|
30 |
+
"DEG",
|
31 |
+
"DER",
|
32 |
+
"DEV",
|
33 |
+
"DT",
|
34 |
+
"ETC",
|
35 |
+
"FW",
|
36 |
+
"IJ",
|
37 |
+
"INF",
|
38 |
+
"JJ",
|
39 |
+
"LB",
|
40 |
+
"LC",
|
41 |
+
"M",
|
42 |
+
"MSP",
|
43 |
+
"NN",
|
44 |
+
"NR",
|
45 |
+
"NT",
|
46 |
+
"OD",
|
47 |
+
"ON",
|
48 |
+
"P",
|
49 |
+
"PN",
|
50 |
+
"PU",
|
51 |
+
"SB",
|
52 |
+
"SP",
|
53 |
+
"URL",
|
54 |
+
"VA",
|
55 |
+
"VC",
|
56 |
+
"VE",
|
57 |
+
"VV",
|
58 |
+
"X"
|
59 |
+
],
|
60 |
+
"parser":[
|
61 |
+
"ROOT",
|
62 |
+
"acl",
|
63 |
+
"advcl:loc",
|
64 |
+
"advmod",
|
65 |
+
"advmod:dvp",
|
66 |
+
"advmod:loc",
|
67 |
+
"advmod:rcomp",
|
68 |
+
"amod",
|
69 |
+
"amod:ordmod",
|
70 |
+
"appos",
|
71 |
+
"aux:asp",
|
72 |
+
"aux:ba",
|
73 |
+
"aux:modal",
|
74 |
+
"aux:prtmod",
|
75 |
+
"auxpass",
|
76 |
+
"case",
|
77 |
+
"cc",
|
78 |
+
"ccomp",
|
79 |
+
"compound:nn",
|
80 |
+
"compound:vc",
|
81 |
+
"conj",
|
82 |
+
"cop",
|
83 |
+
"dep",
|
84 |
+
"det",
|
85 |
+
"discourse",
|
86 |
+
"dobj",
|
87 |
+
"etc",
|
88 |
+
"mark",
|
89 |
+
"mark:clf",
|
90 |
+
"name",
|
91 |
+
"neg",
|
92 |
+
"nmod",
|
93 |
+
"nmod:assmod",
|
94 |
+
"nmod:poss",
|
95 |
+
"nmod:prep",
|
96 |
+
"nmod:range",
|
97 |
+
"nmod:tmod",
|
98 |
+
"nmod:topic",
|
99 |
+
"nsubj",
|
100 |
+
"nsubj:xsubj",
|
101 |
+
"nsubjpass",
|
102 |
+
"nummod",
|
103 |
+
"parataxis:prnmod",
|
104 |
+
"punct",
|
105 |
+
"xcomp"
|
106 |
+
],
|
107 |
+
"attribute_ruler":[
|
108 |
+
|
109 |
+
],
|
110 |
+
"ner":[
|
111 |
+
"CARDINAL",
|
112 |
+
"DATE",
|
113 |
+
"EVENT",
|
114 |
+
"FAC",
|
115 |
+
"GPE",
|
116 |
+
"LANGUAGE",
|
117 |
+
"LAW",
|
118 |
+
"LOC",
|
119 |
+
"MONEY",
|
120 |
+
"NORP",
|
121 |
+
"ORDINAL",
|
122 |
+
"ORG",
|
123 |
+
"PERCENT",
|
124 |
+
"PERSON",
|
125 |
+
"PRODUCT",
|
126 |
+
"QUANTITY",
|
127 |
+
"TIME",
|
128 |
+
"WORK_OF_ART"
|
129 |
+
]
|
130 |
+
},
|
131 |
+
"pipeline":[
|
132 |
+
"transformer",
|
133 |
+
"tagger",
|
134 |
+
"parser",
|
135 |
+
"attribute_ruler",
|
136 |
+
"ner"
|
137 |
+
],
|
138 |
+
"components":[
|
139 |
+
"transformer",
|
140 |
+
"tagger",
|
141 |
+
"parser",
|
142 |
+
"attribute_ruler",
|
143 |
+
"ner"
|
144 |
+
],
|
145 |
+
"disabled":[
|
146 |
+
|
147 |
+
],
|
148 |
+
"performance":{
|
149 |
+
"token_acc":0.9585384056,
|
150 |
+
"token_p":0.9458325855,
|
151 |
+
"token_r":0.9136060443,
|
152 |
+
"token_f":0.9294400505,
|
153 |
+
"tag_acc":0.9175332527,
|
154 |
+
"sents_p":0.7092434038,
|
155 |
+
"sents_r":0.6757116697,
|
156 |
+
"sents_f":0.6920716113,
|
157 |
+
"dep_uas":0.7572203056,
|
158 |
+
"dep_las":0.7145288854,
|
159 |
+
"dep_las_per_type":{
|
160 |
+
"dep":{
|
161 |
+
"p":0.5542676502,
|
162 |
+
"r":0.4251793473,
|
163 |
+
"f":0.4812167648
|
164 |
+
},
|
165 |
+
"case":{
|
166 |
+
"p":0.9020435069,
|
167 |
+
"r":0.8295344326,
|
168 |
+
"f":0.8642708268
|
169 |
+
},
|
170 |
+
"nmod:tmod":{
|
171 |
+
"p":0.7832446809,
|
172 |
+
"r":0.8013605442,
|
173 |
+
"f":0.7921990585
|
174 |
+
},
|
175 |
+
"nummod":{
|
176 |
+
"p":0.8815789474,
|
177 |
+
"r":0.5802798135,
|
178 |
+
"f":0.6998794697
|
179 |
+
},
|
180 |
+
"mark:clf":{
|
181 |
+
"p":0.9339393939,
|
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ner/cfg
ADDED
@@ -0,0 +1,13 @@
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{
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4 |
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6 |
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8 |
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9 |
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|
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ner/model
ADDED
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ner/moves
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οΏ½οΏ½movesοΏ½οΏ½{"0":{},"1":{"GPE":15943,"ORG":15205,"DATE":14256,"PERSON":10912,"CARDINAL":7849,"TIME":2905,"NORP":2685,"EVENT":2602,"MONEY":2519,"LOC":2452,"FAC":2256,"WORK_OF_ART":2014,"QUANTITY":1717,"ORDINAL":1156,"PERCENT":852,"LAW":695,"PRODUCT":486,"LANGUAGE":336},"2":{"GPE":15943,"ORG":15205,"DATE":14256,"PERSON":10912,"CARDINAL":7849,"TIME":2905,"NORP":2685,"EVENT":2602,"MONEY":2519,"LOC":2452,"FAC":2256,"WORK_OF_ART":2014,"QUANTITY":1717,"ORDINAL":1156,"PERCENT":852,"LAW":695,"PRODUCT":486,"LANGUAGE":336},"3":{"GPE":15943,"ORG":15205,"DATE":14256,"PERSON":10912,"CARDINAL":7849,"TIME":2905,"NORP":2685,"EVENT":2602,"MONEY":2519,"LOC":2452,"FAC":2256,"WORK_OF_ART":2014,"QUANTITY":1717,"ORDINAL":1156,"PERCENT":852,"LAW":695,"PRODUCT":486,"LANGUAGE":336},"4":{"GPE":15943,"ORG":15205,"DATE":14256,"PERSON":10912,"CARDINAL":7849,"TIME":2905,"NORP":2685,"EVENT":2602,"MONEY":2519,"LOC":2452,"FAC":2256,"WORK_OF_ART":2014,"QUANTITY":1717,"ORDINAL":1156,"PERCENT":852,"LAW":695,"PRODUCT":486,"LANGUAGE":336,"":1},"5":{"":1}}οΏ½cfgοΏ½οΏ½neg_keyοΏ½
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parser/cfg
ADDED
@@ -0,0 +1,13 @@
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|
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{
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2 |
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4 |
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6 |
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],
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7 |
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8 |
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parser/model
ADDED
Binary file (460 kB). View file
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parser/moves
ADDED
@@ -0,0 +1 @@
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1 |
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tagger/cfg
ADDED
@@ -0,0 +1,43 @@
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|
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|
1 |
+
{
|
2 |
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"label_smoothing":0.0,
|
3 |
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"labels":[
|
4 |
+
"AD",
|
5 |
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|
6 |
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|
7 |
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"CC",
|
8 |
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"CD",
|
9 |
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"CS",
|
10 |
+
"DEC",
|
11 |
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"DEG",
|
12 |
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"DER",
|
13 |
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"DEV",
|
14 |
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"DT",
|
15 |
+
"ETC",
|
16 |
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|
17 |
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"IJ",
|
18 |
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|
19 |
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|
20 |
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"LB",
|
21 |
+
"LC",
|
22 |
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"M",
|
23 |
+
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|
24 |
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|
25 |
+
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|
26 |
+
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|
27 |
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|
28 |
+
"ON",
|
29 |
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|
30 |
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|
31 |
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|
32 |
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|
33 |
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|
34 |
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|
35 |
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|
36 |
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|
37 |
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"VE",
|
38 |
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"VV",
|
39 |
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"X"
|
40 |
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|
41 |
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|
42 |
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|
43 |
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tokenizer/cfg
ADDED
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|
1 |
+
{
|
2 |
+
"segmenter":"pkuseg"
|
3 |
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tokenizer/pkuseg_model/features.msgpack
ADDED
@@ -0,0 +1,3 @@
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size 37508754
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tokenizer/pkuseg_processors
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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transformer/cfg
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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3 |
+
}
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transformer/model
ADDED
@@ -0,0 +1,3 @@
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ADDED
@@ -0,0 +1 @@
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|
1 |
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vocab/lookups.bin
ADDED
@@ -0,0 +1,3 @@
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vocab/strings.json
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vocab/vectors.cfg
ADDED
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|
1 |
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{
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"mode":"default"
|
3 |
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}
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zh_core_web_trf-any-py3-none-any.whl
ADDED
@@ -0,0 +1,3 @@
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