Victoria Slocum commited on
Commit
32163e9
1 Parent(s): d04bf10

Fix:model stuff

Browse files
Files changed (2) hide show
  1. app.py +74 -49
  2. requirements.txt +0 -30
app.py CHANGED
@@ -5,11 +5,16 @@ from spacy.tokens import Span
5
  import gradio as gr
6
 
7
  DEFAULT_MODEL = "en_core_web"
8
- DEFAULT_TEXT = "David Bowie moved to the US in 1974, initially staying in New York City before settling in Los Angeles."
9
  DEFAULT_TOK_ATTR = ['idx', 'text', 'pos_', 'lemma_', 'shape_', 'dep_']
10
  DEFAULT_ENTS = ['CARDINAL', 'DATE', 'EVENT', 'FAC', 'GPE', 'LANGUAGE', 'LAW', 'LOC', 'MONEY',
11
  'NORP', 'ORDINAL', 'ORG', 'PERCENT', 'PERSON', 'PRODUCT', 'QUANTITY', 'TIME', 'WORK_OF_ART']
12
 
 
 
 
 
 
13
 
14
  def get_all_models():
15
  with open("requirements.txt") as f:
@@ -69,84 +74,104 @@ def vectors(text, model):
69
  def span(text, span1, span2, label1, label2, model):
70
  nlp = spacy.load(model + "_sm")
71
  doc = nlp(text)
72
- idx1_1 = 0
73
- idx1_2 = 0
74
- idx2_1 = 0
75
- idx2_2 = 0
76
-
77
- span1 = span1.split(" ")
78
- span2 = span2.split(" ")
79
-
80
- for i in range(len(list(doc))):
81
- tok = list(doc)[i]
82
- if span1[0] == tok.text:
83
- idx1_1 = i
84
- if span1[-1] == tok.text:
85
- idx1_2 = i + 1
86
- if span2[0] == tok.text:
87
- idx2_1 = i
88
- if span2[-1] == tok.text:
89
- idx2_2 = i + 1
90
-
91
- doc.spans["sc"] = [
92
- Span(doc, idx1_1, idx1_2, label1),
93
- Span(doc, idx2_1, idx2_2, label2),
94
- ]
 
 
 
 
 
 
 
 
 
 
 
95
 
96
  html = displacy.render(doc, style="span")
97
  return html
98
 
99
 
 
 
 
 
 
 
 
 
100
  demo = gr.Blocks()
101
 
102
  with demo:
103
- text_input = gr.Textbox(value=DEFAULT_TEXT, interactive=True)
104
  model_input = gr.Dropdown(
105
  choices=models, value=DEFAULT_MODEL, interactive=True)
 
 
 
106
  with gr.Tabs():
107
  with gr.TabItem("Dependency"):
108
  col_punct = gr.Checkbox(label="Collapse Punctuation", value=True)
109
  col_phrase = gr.Checkbox(label="Collapse Phrases", value=True)
110
  compact = gr.Checkbox(label="Compact", value=True)
111
  depen_output = gr.HTML()
112
- depen_button = gr.Button("Generate")
113
  with gr.TabItem("Entity"):
114
  entity_input = gr.CheckboxGroup(DEFAULT_ENTS, value=DEFAULT_ENTS)
115
  entity_output = gr.HTML()
116
- entity_button = gr.Button("Generate")
117
  with gr.TabItem("Tokens"):
118
  with gr.Column():
119
  tok_input = gr.CheckboxGroup(
120
  DEFAULT_TOK_ATTR, value=DEFAULT_TOK_ATTR)
121
  tok_output = gr.Dataframe(
122
  headers=DEFAULT_TOK_ATTR, overflow_row_behaviour="paginate")
123
- tok_button = gr.Button("Generate")
124
  with gr.TabItem("Similarity"):
125
- sim_text1 = gr.Textbox(value="David Bowie", label="Chosen")
126
- sim_text2 = gr.Textbox(value="the US", label="Chosen")
 
127
  sim_output = gr.Textbox(value="0.09", label="Similarity Score")
128
- sim_button = gr.Button("Generate")
129
  with gr.TabItem("Spans"):
130
- with gr.Row():
131
- span1 = gr.Textbox(value="David Bowie", label="Span 1")
132
- label1 = gr.Textbox(value="Name",
133
- label="Label for Span 1")
134
- with gr.Row():
135
- span2 = gr.Textbox(value="David", label="Span 2")
136
- label2 = gr.Textbox(value="First",
137
- label="Label for Span 2")
138
- span_output = gr.HTML()
139
- span_button = gr.Button("Generate")
140
-
141
- depen_button.click(dependency, inputs=[
142
- text_input, col_punct, col_phrase, compact, model_input], outputs=depen_output)
143
- entity_button.click(
 
144
  entity, inputs=[text_input, entity_input, model_input], outputs=entity_output)
145
- tok_button.click(
146
  token, inputs=[text_input, tok_input, model_input], outputs=tok_output)
147
- sim_button.click(vectors, inputs=[text_input, model_input], outputs=[
148
- sim_output, sim_text1, sim_text2])
149
- span_button.click(
150
  span, inputs=[text_input, span1, span2, label1, label2, model_input], outputs=span_output)
151
 
152
  demo.launch()
 
5
  import gradio as gr
6
 
7
  DEFAULT_MODEL = "en_core_web"
8
+ DEFAULT_TEXT = "Apple is looking at buying U.K. startup for $1 billion."
9
  DEFAULT_TOK_ATTR = ['idx', 'text', 'pos_', 'lemma_', 'shape_', 'dep_']
10
  DEFAULT_ENTS = ['CARDINAL', 'DATE', 'EVENT', 'FAC', 'GPE', 'LANGUAGE', 'LAW', 'LOC', 'MONEY',
11
  'NORP', 'ORDINAL', 'ORG', 'PERCENT', 'PERSON', 'PRODUCT', 'QUANTITY', 'TIME', 'WORK_OF_ART']
12
 
13
+ texts = {"en": DEFAULT_TEXT, "ca": "Apple està buscant comprar una startup del Regne Unit per mil milions de dòlars", "da": "Apple overvejer at købe et britisk startup for 1 milliard dollar.", "de": "Die ganze Stadt ist ein Startup: Shenzhen ist das Silicon Valley für Hardware-Firmen",
14
+ "el": "Η άνιση κατανομή του πλούτου και του εισοδήματος, η οποία έχει λάβει τρομερές διαστάσεις, δεν δείχνει τάσεις βελτίωσης.", "es": "Apple está buscando comprar una startup del Reino Unido por mil millones de dólares.", "fi": "Itseajavat autot siirtävät vakuutusvastuun autojen valmistajille", "fr": "Apple cherche à acheter une start-up anglaise pour 1 milliard de dollars", "it": "Apple vuole comprare una startup del Regno Unito per un miliardo di dollari",
15
+ "ja": "アップルがイギリスの新興企業を10億ドルで購入を検討", "ko": "애플이 영국의 스타트업을 10억 달러에 인수하는 것을 알아보고 있다.", "lt": "Jaunikis pirmąją vestuvinę naktį iškeitė į areštinės gultą", "nb": "Apple vurderer å kjøpe britisk oppstartfirma for en milliard dollar.", "nl": "Apple overweegt om voor 1 miljard een U.K. startup te kopen",
16
+ "pl": "Poczuł przyjemną woń mocnej kawy.", "pt": "Apple está querendo comprar uma startup do Reino Unido por 100 milhões de dólares", "ro": "Apple plănuiește să cumpere o companie britanică pentru un miliard de dolari", "ru": "Apple рассматривает возможность покупки стартапа из Соединённого Королевства за $1 млрд", "sv": "Apple överväger att köpa brittisk startup för 1 miljard dollar.", "zh": "作为语言而言,为世界使用人数最多的语言,目前世界有五分之一人口做为母语。"}
17
+
18
 
19
  def get_all_models():
20
  with open("requirements.txt") as f:
 
74
  def span(text, span1, span2, label1, label2, model):
75
  nlp = spacy.load(model + "_sm")
76
  doc = nlp(text)
77
+ if span1:
78
+ idx1_1 = 0
79
+ idx1_2 = 0
80
+ idx2_1 = 0
81
+ idx2_2 = 0
82
+
83
+ span1 = span1.split(" ")
84
+ span2 = span2.split(" ")
85
+
86
+ for i in range(len(list(doc))):
87
+ tok = list(doc)[i]
88
+ if span1[0] == tok.text:
89
+ idx1_1 = i
90
+ if span1[-1] == tok.text:
91
+ idx1_2 = i + 1
92
+ if span2[0] == tok.text:
93
+ idx2_1 = i
94
+ if span2[-1] == tok.text:
95
+ idx2_2 = i + 1
96
+
97
+ doc.spans["sc"] = [
98
+ Span(doc, idx1_1, idx1_2, label1),
99
+ Span(doc, idx2_1, idx2_2, label2),
100
+ ]
101
+ else:
102
+ idx1_1 = 0
103
+ idx1_2 = round(len(list(doc)) / 2)
104
+ idx2_1 = 0
105
+ idx2_2 = 1
106
+
107
+ doc.spans["sc"] = [
108
+ Span(doc, idx1_1, idx1_2, label1),
109
+ Span(doc, idx2_1, idx2_2, label2),
110
+ ]
111
 
112
  html = displacy.render(doc, style="span")
113
  return html
114
 
115
 
116
+ def get_text(model):
117
+ for i in range(len(models)):
118
+ model = model.split("_")[0]
119
+ new_text = texts[model]
120
+
121
+ return new_text
122
+
123
+
124
  demo = gr.Blocks()
125
 
126
  with demo:
 
127
  model_input = gr.Dropdown(
128
  choices=models, value=DEFAULT_MODEL, interactive=True)
129
+ text_button = gr.Button("Get new text")
130
+ text_input = gr.Textbox(value=DEFAULT_TEXT, interactive=True)
131
+ button = gr.Button("Generate")
132
  with gr.Tabs():
133
  with gr.TabItem("Dependency"):
134
  col_punct = gr.Checkbox(label="Collapse Punctuation", value=True)
135
  col_phrase = gr.Checkbox(label="Collapse Phrases", value=True)
136
  compact = gr.Checkbox(label="Compact", value=True)
137
  depen_output = gr.HTML()
138
+
139
  with gr.TabItem("Entity"):
140
  entity_input = gr.CheckboxGroup(DEFAULT_ENTS, value=DEFAULT_ENTS)
141
  entity_output = gr.HTML()
 
142
  with gr.TabItem("Tokens"):
143
  with gr.Column():
144
  tok_input = gr.CheckboxGroup(
145
  DEFAULT_TOK_ATTR, value=DEFAULT_TOK_ATTR)
146
  tok_output = gr.Dataframe(
147
  headers=DEFAULT_TOK_ATTR, overflow_row_behaviour="paginate")
 
148
  with gr.TabItem("Similarity"):
149
+ with gr.Row():
150
+ sim_text1 = gr.Textbox(value="David Bowie", label="Chosen")
151
+ sim_text2 = gr.Textbox(value="the US", label="Chosen")
152
  sim_output = gr.Textbox(value="0.09", label="Similarity Score")
 
153
  with gr.TabItem("Spans"):
154
+ with gr.Column():
155
+ with gr.Row():
156
+ span1 = gr.Textbox(label="Span 1")
157
+ label1 = gr.Textbox(value="Label 1",
158
+ label="Label for Span 1")
159
+ with gr.Row():
160
+ span2 = gr.Textbox(label="Span 2")
161
+ label2 = gr.Textbox(value="Label 2",
162
+ label="Label for Span 2")
163
+ with gr.Row():
164
+ span_output = gr.HTML()
165
+ text_button.click(get_text, inputs=[model_input], outputs=text_input)
166
+ button.click(dependency, inputs=[
167
+ text_input, col_punct, col_phrase, compact, model_input], outputs=depen_output)
168
+ button.click(
169
  entity, inputs=[text_input, entity_input, model_input], outputs=entity_output)
170
+ button.click(
171
  token, inputs=[text_input, tok_input, model_input], outputs=tok_output)
172
+ button.click(vectors, inputs=[text_input, model_input], outputs=[
173
+ sim_output, sim_text1, sim_text2])
174
+ button.click(
175
  span, inputs=[text_input, span1, span2, label1, label2, model_input], outputs=span_output)
176
 
177
  demo.launch()
requirements.txt CHANGED
@@ -2,45 +2,30 @@
2
  gradio==3.0.18
3
  spacy==3.3.1
4
 
5
- https://huggingface.co/spacy/ca_core_news_lg/resolve/main/ca_core_news_lg-any-py3-none-any.whl
6
  https://huggingface.co/spacy/ca_core_news_md/resolve/main/ca_core_news_md-any-py3-none-any.whl
7
  https://huggingface.co/spacy/ca_core_news_sm/resolve/main/ca_core_news_sm-any-py3-none-any.whl
8
- https://huggingface.co/spacy/ca_core_news_trf/resolve/main/ca_core_news_trf-any-py3-none-any.whl
9
 
10
- https://huggingface.co/spacy/da_core_news_lg/resolve/main/da_core_news_lg-any-py3-none-any.whl
11
  https://huggingface.co/spacy/da_core_news_md/resolve/main/da_core_news_md-any-py3-none-any.whl
12
  https://huggingface.co/spacy/da_core_news_sm/resolve/main/da_core_news_sm-any-py3-none-any.whl
13
- https://huggingface.co/spacy/da_core_news_trf/resolve/main/da_core_news_trf-any-py3-none-any.whl
14
 
15
- https://huggingface.co/spacy/de_core_news_lg/resolve/main/de_core_news_lg-any-py3-none-any.whl
16
  https://huggingface.co/spacy/de_core_news_md/resolve/main/de_core_news_md-any-py3-none-any.whl
17
  https://huggingface.co/spacy/de_core_news_sm/resolve/main/de_core_news_sm-any-py3-none-any.whl
18
- https://huggingface.co/spacy/de_dep_news_trf/resolve/main/de_dep_news_trf-any-py3-none-any.whl
19
 
20
- https://huggingface.co/spacy/el_core_news_lg/resolve/main/el_core_news_lg-any-py3-none-any.whl
21
  https://huggingface.co/spacy/el_core_news_md/resolve/main/el_core_news_md-any-py3-none-any.whl
22
  https://huggingface.co/spacy/el_core_news_sm/resolve/main/el_core_news_sm-any-py3-none-any.whl
23
 
24
- https://huggingface.co/spacy/en_core_web_lg/resolve/main/en_core_web_lg-any-py3-none-any.whl
25
  https://huggingface.co/spacy/en_core_web_md/resolve/main/en_core_web_md-any-py3-none-any.whl
26
  https://huggingface.co/spacy/en_core_web_sm/resolve/main/en_core_web_sm-any-py3-none-any.whl
27
- https://huggingface.co/spacy/en_core_web_trf/resolve/main/en_core_web_trf-any-py3-none-any.whl
28
 
29
- https://huggingface.co/spacy/es_core_news_lg/resolve/main/es_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/es_core_news_md/resolve/main/es_core_news_md-any-py3-none-any.whl
31
  https://huggingface.co/spacy/es_core_news_sm/resolve/main/es_core_news_sm-any-py3-none-any.whl
32
- https://huggingface.co/spacy/es_dep_news_trf/resolve/main/es_dep_news_trf-any-py3-none-any.whl
33
 
34
- https://huggingface.co/spacy/fi_core_news_lg/resolve/main/fi_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/fi_core_news_md/resolve/main/fi_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/fi_core_news_sm/resolve/main/fi_core_news_sm-any-py3-none-any.whl
37
 
38
- https://huggingface.co/spacy/fr_core_news_lg/resolve/main/fr_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/fr_core_news_md/resolve/main/fr_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/fr_core_news_sm/resolve/main/fr_core_news_sm-any-py3-none-any.whl
41
- https://huggingface.co/spacy/fr_dep_news_trf/resolve/main/fr_dep_news_trf-any-py3-none-any.whl
42
 
43
- https://huggingface.co/spacy/it_core_news_lg/resolve/main/it_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/it_core_news_md/resolve/main/it_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/it_core_news_sm/resolve/main/it_core_news_sm-any-py3-none-any.whl
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@@ -48,47 +33,32 @@ https://huggingface.co/spacy/ja_core_news_lg/resolve/main/ja_core_news_lg-any-py
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  https://huggingface.co/spacy/ja_core_news_md/resolve/main/ja_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/ja_core_news_sm/resolve/main/ja_core_news_sm-any-py3-none-any.whl
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51
- https://huggingface.co/spacy/ko_core_news_lg/resolve/main/ko_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/ko_core_news_md/resolve/main/ko_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/ko_core_news_sm/resolve/main/ko_core_news_sm-any-py3-none-any.whl
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- https://huggingface.co/spacy/lt_core_news_lg/resolve/main/lt_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/lt_core_news_md/resolve/main/lt_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/lt_core_news_sm/resolve/main/lt_core_news_sm-any-py3-none-any.whl
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- https://huggingface.co/spacy/mk_core_news_lg/resolve/main/mk_core_news_lg-any-py3-none-any.whl
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- https://huggingface.co/spacy/mk_core_news_md/resolve/main/mk_core_news_md-any-py3-none-any.whl
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- https://huggingface.co/spacy/mk_core_news_sm/resolve/main/mk_core_news_sm-any-py3-none-any.whl
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-
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- https://huggingface.co/spacy/nb_core_news_lg/resolve/main/nb_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/nb_core_news_md/resolve/main/nb_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/nb_core_news_sm/resolve/main/nb_core_news_sm-any-py3-none-any.whl
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- https://huggingface.co/spacy/nl_core_news_lg/resolve/main/nl_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/nl_core_news_md/resolve/main/nl_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/nl_core_news_sm/resolve/main/nl_core_news_sm-any-py3-none-any.whl
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71
- https://huggingface.co/spacy/pl_core_news_lg/resolve/main/pl_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/pl_core_news_md/resolve/main/pl_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/pl_core_news_sm/resolve/main/pl_core_news_sm-any-py3-none-any.whl
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75
- https://huggingface.co/spacy/pt_core_news_lg/resolve/main/pt_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/pt_core_news_md/resolve/main/pt_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/pt_core_news_sm/resolve/main/pt_core_news_sm-any-py3-none-any.whl
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79
- https://huggingface.co/spacy/ro_core_news_lg/resolve/main/ro_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/ro_core_news_md/resolve/main/ro_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/ro_core_news_sm/resolve/main/ro_core_news_sm-any-py3-none-any.whl
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83
- https://huggingface.co/spacy/ru_core_news_lg/resolve/main/ru_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/ru_core_news_md/resolve/main/ru_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/ru_core_news_sm/resolve/main/ru_core_news_sm-any-py3-none-any.whl
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- https://huggingface.co/spacy/sv_core_news_lg/resolve/main/sv_core_news_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/sv_core_news_md/resolve/main/sv_core_news_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/sv_core_news_sm/resolve/main/sv_core_news_sm-any-py3-none-any.whl
90
 
91
- https://huggingface.co/spacy/zh_core_web_lg/resolve/main/zh_core_web_lg-any-py3-none-any.whl
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  https://huggingface.co/spacy/zh_core_web_md/resolve/main/zh_core_web_md-any-py3-none-any.whl
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  https://huggingface.co/spacy/zh_core_web_sm/resolve/main/zh_core_web_sm-any-py3-none-any.whl
94
- https://huggingface.co/spacy/zh_core_web_trf/resolve/main/zh_core_web_trf-any-py3-none-any.whl
 
2
  gradio==3.0.18
3
  spacy==3.3.1
4
 
 
5
  https://huggingface.co/spacy/ca_core_news_md/resolve/main/ca_core_news_md-any-py3-none-any.whl
6
  https://huggingface.co/spacy/ca_core_news_sm/resolve/main/ca_core_news_sm-any-py3-none-any.whl
 
7
 
 
8
  https://huggingface.co/spacy/da_core_news_md/resolve/main/da_core_news_md-any-py3-none-any.whl
9
  https://huggingface.co/spacy/da_core_news_sm/resolve/main/da_core_news_sm-any-py3-none-any.whl
 
10
 
 
11
  https://huggingface.co/spacy/de_core_news_md/resolve/main/de_core_news_md-any-py3-none-any.whl
12
  https://huggingface.co/spacy/de_core_news_sm/resolve/main/de_core_news_sm-any-py3-none-any.whl
 
13
 
 
14
  https://huggingface.co/spacy/el_core_news_md/resolve/main/el_core_news_md-any-py3-none-any.whl
15
  https://huggingface.co/spacy/el_core_news_sm/resolve/main/el_core_news_sm-any-py3-none-any.whl
16
 
 
17
  https://huggingface.co/spacy/en_core_web_md/resolve/main/en_core_web_md-any-py3-none-any.whl
18
  https://huggingface.co/spacy/en_core_web_sm/resolve/main/en_core_web_sm-any-py3-none-any.whl
 
19
 
 
20
  https://huggingface.co/spacy/es_core_news_md/resolve/main/es_core_news_md-any-py3-none-any.whl
21
  https://huggingface.co/spacy/es_core_news_sm/resolve/main/es_core_news_sm-any-py3-none-any.whl
 
22
 
 
23
  https://huggingface.co/spacy/fi_core_news_md/resolve/main/fi_core_news_md-any-py3-none-any.whl
24
  https://huggingface.co/spacy/fi_core_news_sm/resolve/main/fi_core_news_sm-any-py3-none-any.whl
25
 
 
26
  https://huggingface.co/spacy/fr_core_news_md/resolve/main/fr_core_news_md-any-py3-none-any.whl
27
  https://huggingface.co/spacy/fr_core_news_sm/resolve/main/fr_core_news_sm-any-py3-none-any.whl
 
28
 
 
29
  https://huggingface.co/spacy/it_core_news_md/resolve/main/it_core_news_md-any-py3-none-any.whl
30
  https://huggingface.co/spacy/it_core_news_sm/resolve/main/it_core_news_sm-any-py3-none-any.whl
31
 
 
33
  https://huggingface.co/spacy/ja_core_news_md/resolve/main/ja_core_news_md-any-py3-none-any.whl
34
  https://huggingface.co/spacy/ja_core_news_sm/resolve/main/ja_core_news_sm-any-py3-none-any.whl
35
 
 
36
  https://huggingface.co/spacy/ko_core_news_md/resolve/main/ko_core_news_md-any-py3-none-any.whl
37
  https://huggingface.co/spacy/ko_core_news_sm/resolve/main/ko_core_news_sm-any-py3-none-any.whl
38
 
 
39
  https://huggingface.co/spacy/lt_core_news_md/resolve/main/lt_core_news_md-any-py3-none-any.whl
40
  https://huggingface.co/spacy/lt_core_news_sm/resolve/main/lt_core_news_sm-any-py3-none-any.whl
41
 
 
 
 
 
 
42
  https://huggingface.co/spacy/nb_core_news_md/resolve/main/nb_core_news_md-any-py3-none-any.whl
43
  https://huggingface.co/spacy/nb_core_news_sm/resolve/main/nb_core_news_sm-any-py3-none-any.whl
44
 
 
45
  https://huggingface.co/spacy/nl_core_news_md/resolve/main/nl_core_news_md-any-py3-none-any.whl
46
  https://huggingface.co/spacy/nl_core_news_sm/resolve/main/nl_core_news_sm-any-py3-none-any.whl
47
 
 
48
  https://huggingface.co/spacy/pl_core_news_md/resolve/main/pl_core_news_md-any-py3-none-any.whl
49
  https://huggingface.co/spacy/pl_core_news_sm/resolve/main/pl_core_news_sm-any-py3-none-any.whl
50
 
 
51
  https://huggingface.co/spacy/pt_core_news_md/resolve/main/pt_core_news_md-any-py3-none-any.whl
52
  https://huggingface.co/spacy/pt_core_news_sm/resolve/main/pt_core_news_sm-any-py3-none-any.whl
53
 
 
54
  https://huggingface.co/spacy/ro_core_news_md/resolve/main/ro_core_news_md-any-py3-none-any.whl
55
  https://huggingface.co/spacy/ro_core_news_sm/resolve/main/ro_core_news_sm-any-py3-none-any.whl
56
 
 
57
  https://huggingface.co/spacy/ru_core_news_md/resolve/main/ru_core_news_md-any-py3-none-any.whl
58
  https://huggingface.co/spacy/ru_core_news_sm/resolve/main/ru_core_news_sm-any-py3-none-any.whl
59
 
 
60
  https://huggingface.co/spacy/sv_core_news_md/resolve/main/sv_core_news_md-any-py3-none-any.whl
61
  https://huggingface.co/spacy/sv_core_news_sm/resolve/main/sv_core_news_sm-any-py3-none-any.whl
62
 
 
63
  https://huggingface.co/spacy/zh_core_web_md/resolve/main/zh_core_web_md-any-py3-none-any.whl
64
  https://huggingface.co/spacy/zh_core_web_sm/resolve/main/zh_core_web_sm-any-py3-none-any.whl