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  1. README.md +7 -5
README.md CHANGED
@@ -5,13 +5,15 @@ tags:
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  - opt
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  - custom-license
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  - no-commercial
 
 
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  datasets:
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  - aeslc
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  widget:
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- - text: "Hey <NAME>,\n\nThank you for signing up to my weekly newsletter. Before we get started, youll have to confirm your email address."
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  example_title: "newsletter"
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- - text: "Hi <NAME>,\n\nI hope this email finds you well. Let me start by saying that I am a big fan of your work"
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  example_title: "fan"
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  - text: "Greetings <NAME>,\n\nI hope you had a splendid evening at the Company sausage eating festival. I am reaching out because"
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  example_title: "festival"
@@ -61,12 +63,12 @@ generator(prompt) # generate
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  ## Model description
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  - This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the [aeslc](https://huggingface.co/datasets/aeslc) dataset for six epochs.
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- - Emails, phone numbers, etc were attempted to be excluded in a dataset preparation step using [clean-text](https://pypi.org/project/clean-text/) in Python.
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- - Note that API is restricted to generate 64 tokens - you can generate longer emails by using this in a text-generation `pipeline` object
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  ## Intended uses & limitations
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- - in their everlasting wisdom, Facebook/Meta has decided to make a custom license for this specifying several things. See [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) for details.
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  ## Training and evaluation data
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  - opt
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  - custom-license
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  - no-commercial
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+ - email
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+ - auto-complete
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  datasets:
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  - aeslc
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  widget:
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+ - text: "Hey <NAME>,\n\nThank you for signing up for my weekly newsletter. Before we get started, you'll have to confirm your email address."
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  example_title: "newsletter"
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+ - text: "Hi <NAME>,\n\nI hope this email finds you well. Let me start by saying that I am a big fan of your work."
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  example_title: "fan"
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  - text: "Greetings <NAME>,\n\nI hope you had a splendid evening at the Company sausage eating festival. I am reaching out because"
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  example_title: "festival"
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  ## Model description
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  - This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the [aeslc](https://huggingface.co/datasets/aeslc) dataset for six epochs.
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+ - Emails, phone numbers, etc., were attempted to be excluded in a dataset preparation step using [clean-text](https://pypi.org/project/clean-text/) in Python.
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+ - Note that API is restricted to generating 64 tokens - you can generate longer emails by using this in a text-generation `pipeline` object
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  ## Intended uses & limitations
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+ - in their everlasting wisdom, Facebook/Meta has decided to make a custom license for this, specifying several things. See [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) for details.
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  ## Training and evaluation data
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