Librarian Bot: Add base_model information to model

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  1. README.md +54 -112
README.md CHANGED
@@ -1,134 +1,74 @@
1
  ---
 
 
2
  license:
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  - apache-2.0
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  - cc-by-nc-4.0
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- datasets: pszemraj/fleece2instructions-codealpaca
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  tags:
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  - generated_from_trainer
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  - instruct
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  - instructions
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  - code
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  - instructiongen
 
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  metrics:
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  - rouge
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- language:
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- - en
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  widget:
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- - text: |
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- git lfs install
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  huggingface-cli lfs-enable-largefiles .
 
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  git lfs track "*.bin"
 
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  git add .
 
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  git commit -a -m "add fp32 chkpt"
 
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  git push
 
 
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  example_title: bash
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- - text: |
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- export interface DocumentParams {
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- pageContent: string;
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-
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- // eslint-disable-next-line @typescript-eslint/no-explicit-any
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- metadata: Record<string, any>;
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- }
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-
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- /**
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- * Interface for interacting with a document.
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- */
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- export class Document implements DocumentParams {
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- pageContent: string;
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-
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- // eslint-disable-next-line @typescript-eslint/no-explicit-any
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- metadata: Record<string, any>;
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-
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- constructor(fields?: Partial<DocumentParams>) {
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- this.pageContent = fields?.pageContent ?? this.pageContent;
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- this.metadata = fields?.metadata ?? {};
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- }
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- }
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  example_title: js
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- - text: |
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- def merge(left, right):
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- if len(left) == 0:
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- return right
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-
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- if len(right) == 0:
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- return left
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-
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- result = []
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- index_left = index_right = 0
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-
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- while len(result) < len(left) + len(right):
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- if left[index_left] <= right[index_right]:
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- result.append(left[index_left])
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- index_left += 1
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- else:
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- result.append(right[index_right])
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- index_right += 1
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-
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- if index_right == len(right):
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- result += left[index_left:]
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- break
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-
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- if index_left == len(left):
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- result += right[index_right:]
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- break
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-
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- return result
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  example_title: merge
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- - text: >
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- import pandas as pd
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-
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- import plotly.graph_objects as go
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-
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-
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- df =
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- pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_apple_stock.csv')
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-
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-
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- fig = go.Figure(go.Scatter(x = df['AAPL_x'], y = df['AAPL_y'],
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- name='Share Prices (in USD)'))
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-
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- fig.update_layout(title='Apple Share Prices over time (2014)',
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- plot_bgcolor='rgb(230, 230,230)',
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- showlegend=True)
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-
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- fig.show()
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  example_title: plot
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- - text: |
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- from spellchecker import SpellChecker
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-
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- spell = SpellChecker()
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-
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- def check_word_spelling(word: str):
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- misspelled = spell.unknown([word])
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- return len(misspelled) == 0
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-
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- def eval_and_replace(text: str, match_token: str = "- "):
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- if match_token not in text:
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- return text
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- else:
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- while True:
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- full_before_text = text.split(match_token, maxsplit=1)[0]
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- before_text = [
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- char for char in full_before_text.split()[-1] if char.isalpha()
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- ]
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- before_text = "".join(before_text)
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- full_after_text = text.split(match_token, maxsplit=1)[-1]
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- after_text = [char for char in full_after_text.split()[0] if char.isalpha()]
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- after_text = "".join(after_text)
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- full_text = before_text + after_text
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- if check_word_spelling(full_text):
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- text = full_before_text + full_after_text
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- else:
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- text = full_before_text + " " + full_after_text
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- if match_token not in text:
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- break
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- return text
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-
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- text = "I- am- a go- od- boy"
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- eval_and_replace(text)
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  example_title: spell check
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- - text: >
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- import torch
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  from transformers import AutoTokenizer, AutoModelForSequenceClassification
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@@ -139,19 +79,21 @@ widget:
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  model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
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- sequences = ["I've been waiting for a HuggingFace course my whole life.",
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- "So have I!"]
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145
 
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- tokens = tokenizer(sequences, padding=True, truncation=True,
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- return_tensors="pt")
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149
  output = model(**tokens)
 
 
150
  example_title: model inference
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  inference:
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  parameters:
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  max_length: 96
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  num_beams: 4
 
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  ---
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
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+
19
  huggingface-cli lfs-enable-largefiles .
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+
21
  git lfs track "*.bin"
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+
23
  git add .
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+
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  git commit -a -m "add fp32 chkpt"
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+
27
  git push
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+
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+ '
30
  example_title: bash
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+ - text: "export interface DocumentParams {\n pageContent: string;\n\n // eslint-disable-next-line\
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+ \ @typescript-eslint/no-explicit-any\n metadata: Record<string, any>;\n}\n\n\
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+ /**\n * Interface for interacting with a document.\n */\nexport class Document\
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+ \ implements DocumentParams {\n pageContent: string;\n\n // eslint-disable-next-line\
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+ \ @typescript-eslint/no-explicit-any\n metadata: Record<string, any>;\n\n constructor(fields?:\
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+ \ Partial<DocumentParams>) {\n this.pageContent = fields?.pageContent ?? this.pageContent;\n\
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+ \ this.metadata = fields?.metadata ?? {};\n }\n}\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  example_title: js
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+ - text: "def merge(left, right):\n if len(left) == 0:\n return right\n\n\
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+ \ if len(right) == 0:\n return left\n\n result = []\n index_left\
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+ \ = index_right = 0\n\n while len(result) < len(left) + len(right):\n \
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+ \ if left[index_left] <= right[index_right]:\n result.append(left[index_left])\n\
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+ \ index_left += 1\n else:\n result.append(right[index_right])\n\
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+ \ index_right += 1\n\n if index_right == len(right):\n \
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+ \ result += left[index_left:]\n break\n\n if index_left\
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+ \ == len(left):\n result += right[index_right:]\n break\n\
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+ \n return result\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  example_title: merge
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+ - 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\
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+ \nfig = go.Figure(go.Scatter(x = df['AAPL_x'], y = df['AAPL_y'],\n \
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+ \ name='Share Prices (in USD)'))\n\nfig.update_layout(title='Apple Share\
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+ \ Prices over time (2014)',\n plot_bgcolor='rgb(230, 230,230)',\n\
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+ \ showlegend=True)\n\nfig.show()\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
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  example_title: plot
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+ - text: "from spellchecker import SpellChecker\n\nspell = SpellChecker()\n\ndef check_word_spelling(word:\
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+ \ str):\n misspelled = spell.unknown([word])\n return len(misspelled) ==\
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+ \ 0\n\ndef eval_and_replace(text: str, match_token: str = \"- \"):\n if match_token\
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+ \ not in text:\n return text\n else:\n while True:\n \
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+ \ full_before_text = text.split(match_token, maxsplit=1)[0]\n before_text\
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+ \ = [\n char for char in full_before_text.split()[-1] if char.isalpha()\n\
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+ \ ]\n before_text = \"\".join(before_text)\n \
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+ \ full_after_text = text.split(match_token, maxsplit=1)[-1]\n after_text\
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+ \ = [char for char in full_after_text.split()[0] if char.isalpha()]\n \
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+ \ after_text = \"\".join(after_text)\n full_text = before_text +\
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+ \ after_text\n if check_word_spelling(full_text):\n \
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+ \ text = full_before_text + full_after_text\n else:\n \
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+ \ text = full_before_text + \" \" + full_after_text\n if match_token\
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+ \ not in text:\n break\n return text\n\ntext = \"I- am-\
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+ \ a go- od- boy\"\neval_and_replace(text)\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
70
  example_title: spell check
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+ - 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
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+ have I!"]
84
 
85
 
86
+ tokens = tokenizer(sequences, padding=True, truncation=True, return_tensors="pt")
 
87
 
88
  output = model(**tokens)
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+
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+ '
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  example_title: model inference
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  inference:
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  parameters:
94
  max_length: 96
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  num_beams: 4
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+ base_model: facebook/bart-base
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  ---
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