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Librarian Bot: Add base_model information to model

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This pull request aims to enrich the metadata of your model by adding [`facebook/bart-base`](https://huggingface.co/facebook/bart-base) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.

How did we find this information? We performed a regular expression match on your `README.md` file to determine the connection.

**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.

For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).

This PR was requested via the [Librarian Bot](https://huggingface.co/librarian-bot) [metadata request service](https://huggingface.co/spaces/librarian-bots/metadata_request_service) by request of [davanstrien](https://huggingface.co/davanstrien)

Files changed (1) hide show
  1. README.md +54 -112
README.md CHANGED
@@ -1,134 +1,74 @@
1
  ---
 
 
2
  license:
3
  - apache-2.0
4
  - cc-by-nc-4.0
5
- datasets: pszemraj/fleece2instructions-codealpaca
6
  tags:
7
  - generated_from_trainer
8
  - instruct
9
  - instructions
10
  - code
11
  - instructiongen
 
12
  metrics:
13
  - rouge
14
- language:
15
- - en
16
  widget:
17
- - text: |
18
- git lfs install
19
  huggingface-cli lfs-enable-largefiles .
 
20
  git lfs track "*.bin"
 
21
  git add .
 
22
  git commit -a -m "add fp32 chkpt"
 
23
  git push
 
 
24
  example_title: bash
25
- - text: |
26
- export interface DocumentParams {
27
- pageContent: string;
28
-
29
- // eslint-disable-next-line @typescript-eslint/no-explicit-any
30
- metadata: Record<string, any>;
31
- }
32
-
33
- /**
34
- * Interface for interacting with a document.
35
- */
36
- export class Document implements DocumentParams {
37
- pageContent: string;
38
-
39
- // eslint-disable-next-line @typescript-eslint/no-explicit-any
40
- metadata: Record<string, any>;
41
-
42
- constructor(fields?: Partial<DocumentParams>) {
43
- this.pageContent = fields?.pageContent ?? this.pageContent;
44
- this.metadata = fields?.metadata ?? {};
45
- }
46
- }
47
  example_title: js
48
- - text: |
49
- def merge(left, right):
50
- if len(left) == 0:
51
- return right
52
-
53
- if len(right) == 0:
54
- return left
55
-
56
- result = []
57
- index_left = index_right = 0
58
-
59
- while len(result) < len(left) + len(right):
60
- if left[index_left] <= right[index_right]:
61
- result.append(left[index_left])
62
- index_left += 1
63
- else:
64
- result.append(right[index_right])
65
- index_right += 1
66
-
67
- if index_right == len(right):
68
- result += left[index_left:]
69
- break
70
-
71
- if index_left == len(left):
72
- result += right[index_right:]
73
- break
74
-
75
- return result
76
  example_title: merge
77
- - text: >
78
- import pandas as pd
79
-
80
- import plotly.graph_objects as go
81
-
82
-
83
- df =
84
- pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_apple_stock.csv')
85
-
86
-
87
- fig = go.Figure(go.Scatter(x = df['AAPL_x'], y = df['AAPL_y'],
88
- name='Share Prices (in USD)'))
89
-
90
- fig.update_layout(title='Apple Share Prices over time (2014)',
91
- plot_bgcolor='rgb(230, 230,230)',
92
- showlegend=True)
93
-
94
- fig.show()
95
  example_title: plot
96
- - text: |
97
- from spellchecker import SpellChecker
98
-
99
- spell = SpellChecker()
100
-
101
- def check_word_spelling(word: str):
102
- misspelled = spell.unknown([word])
103
- return len(misspelled) == 0
104
-
105
- def eval_and_replace(text: str, match_token: str = "- "):
106
- if match_token not in text:
107
- return text
108
- else:
109
- while True:
110
- full_before_text = text.split(match_token, maxsplit=1)[0]
111
- before_text = [
112
- char for char in full_before_text.split()[-1] if char.isalpha()
113
- ]
114
- before_text = "".join(before_text)
115
- full_after_text = text.split(match_token, maxsplit=1)[-1]
116
- after_text = [char for char in full_after_text.split()[0] if char.isalpha()]
117
- after_text = "".join(after_text)
118
- full_text = before_text + after_text
119
- if check_word_spelling(full_text):
120
- text = full_before_text + full_after_text
121
- else:
122
- text = full_before_text + " " + full_after_text
123
- if match_token not in text:
124
- break
125
- return text
126
-
127
- text = "I- am- a go- od- boy"
128
- eval_and_replace(text)
129
  example_title: spell check
130
- - text: >
131
- import torch
132
 
133
  from transformers import AutoTokenizer, AutoModelForSequenceClassification
134
 
@@ -139,19 +79,21 @@ widget:
139
 
140
  model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
141
 
142
- sequences = ["I've been waiting for a HuggingFace course my whole life.",
143
- "So have I!"]
144
 
145
 
146
- tokens = tokenizer(sequences, padding=True, truncation=True,
147
- return_tensors="pt")
148
 
149
  output = model(**tokens)
 
 
150
  example_title: model inference
151
  inference:
152
  parameters:
153
  max_length: 96
154
  num_beams: 4
 
155
  ---
156
 
157
 
 
1
  ---
2
+ language:
3
+ - en
4
  license:
5
  - apache-2.0
6
  - cc-by-nc-4.0
 
7
  tags:
8
  - generated_from_trainer
9
  - instruct
10
  - instructions
11
  - code
12
  - instructiongen
13
+ datasets: pszemraj/fleece2instructions-codealpaca
14
  metrics:
15
  - rouge
 
 
16
  widget:
17
+ - text: 'git lfs install
18
+
19
  huggingface-cli lfs-enable-largefiles .
20
+
21
  git lfs track "*.bin"
22
+
23
  git add .
24
+
25
  git commit -a -m "add fp32 chkpt"
26
+
27
  git push
28
+
29
+ '
30
  example_title: bash
31
+ - text: "export interface DocumentParams {\n pageContent: string;\n\n // eslint-disable-next-line\
32
+ \ @typescript-eslint/no-explicit-any\n metadata: Record<string, any>;\n}\n\n\
33
+ /**\n * Interface for interacting with a document.\n */\nexport class Document\
34
+ \ implements DocumentParams {\n pageContent: string;\n\n // eslint-disable-next-line\
35
+ \ @typescript-eslint/no-explicit-any\n metadata: Record<string, any>;\n\n constructor(fields?:\
36
+ \ Partial<DocumentParams>) {\n this.pageContent = fields?.pageContent ?? this.pageContent;\n\
37
+ \ this.metadata = fields?.metadata ?? {};\n }\n}\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
38
  example_title: js
39
+ - text: "def merge(left, right):\n if len(left) == 0:\n return right\n\n\
40
+ \ if len(right) == 0:\n return left\n\n result = []\n index_left\
41
+ \ = index_right = 0\n\n while len(result) < len(left) + len(right):\n \
42
+ \ if left[index_left] <= right[index_right]:\n result.append(left[index_left])\n\
43
+ \ index_left += 1\n else:\n result.append(right[index_right])\n\
44
+ \ index_right += 1\n\n if index_right == len(right):\n \
45
+ \ result += left[index_left:]\n break\n\n if index_left\
46
+ \ == len(left):\n result += right[index_right:]\n break\n\
47
+ \n return result\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
48
  example_title: merge
49
+ - text: "import pandas as pd\nimport plotly.graph_objects as go\n\ndf = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_apple_stock.csv')\n\
50
+ \nfig = go.Figure(go.Scatter(x = df['AAPL_x'], y = df['AAPL_y'],\n \
51
+ \ name='Share Prices (in USD)'))\n\nfig.update_layout(title='Apple Share\
52
+ \ Prices over time (2014)',\n plot_bgcolor='rgb(230, 230,230)',\n\
53
+ \ showlegend=True)\n\nfig.show()\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
54
  example_title: plot
55
+ - text: "from spellchecker import SpellChecker\n\nspell = SpellChecker()\n\ndef check_word_spelling(word:\
56
+ \ str):\n misspelled = spell.unknown([word])\n return len(misspelled) ==\
57
+ \ 0\n\ndef eval_and_replace(text: str, match_token: str = \"- \"):\n if match_token\
58
+ \ not in text:\n return text\n else:\n while True:\n \
59
+ \ full_before_text = text.split(match_token, maxsplit=1)[0]\n before_text\
60
+ \ = [\n char for char in full_before_text.split()[-1] if char.isalpha()\n\
61
+ \ ]\n before_text = \"\".join(before_text)\n \
62
+ \ full_after_text = text.split(match_token, maxsplit=1)[-1]\n after_text\
63
+ \ = [char for char in full_after_text.split()[0] if char.isalpha()]\n \
64
+ \ after_text = \"\".join(after_text)\n full_text = before_text +\
65
+ \ after_text\n if check_word_spelling(full_text):\n \
66
+ \ text = full_before_text + full_after_text\n else:\n \
67
+ \ text = full_before_text + \" \" + full_after_text\n if match_token\
68
+ \ not in text:\n break\n return text\n\ntext = \"I- am-\
69
+ \ a go- od- boy\"\neval_and_replace(text)\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
70
  example_title: spell check
71
+ - text: 'import torch
 
72
 
73
  from transformers import AutoTokenizer, AutoModelForSequenceClassification
74
 
 
79
 
80
  model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
81
 
82
+ sequences = ["I''ve been waiting for a HuggingFace course my whole life.", "So
83
+ have I!"]
84
 
85
 
86
+ tokens = tokenizer(sequences, padding=True, truncation=True, return_tensors="pt")
 
87
 
88
  output = model(**tokens)
89
+
90
+ '
91
  example_title: model inference
92
  inference:
93
  parameters:
94
  max_length: 96
95
  num_beams: 4
96
+ base_model: facebook/bart-base
97
  ---
98
 
99