Add files via upload #82
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
We wrote a Python script to calculate the perplexity of a sentence using the GPT-2 model from the Hugging Face Transformers library. The script imports necessary libraries, loads the model and tokenizer, and defines a function that tokenizes input text, computes the model's loss, and derives perplexity from that loss. We tested the function with an example sentence, outputting a perplexity value that indicates how predictable the model finds the text. This process helps evaluate the model's understanding of language based on its training.
|
@tarun-aiplanet please check and verify |
|
This is isn't how the LLM support is added. Check #81 Check LLM folder. Furthermore, by Perplexity I mean perplexity.ai model using API support. |
|
I am closing this PR, as its irrelevant code addition. |
|
can we do it without api support |
|
like genrating text without api support |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
We wrote a Python script to calculate the perplexity of a sentence using the GPT-2 model from the Hugging Face Transformers library. The script imports necessary libraries, loads the model and tokenizer, and defines a function that tokenizes input text, computes the model's loss, and derives perplexity from that loss. We tested the function with an example sentence, outputting a perplexity value that indicates how predictable the model finds the text. This process helps evaluate the model's understanding of language based on its training.