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APIs and batch processing ‐ second collaboratory session
Please read Jacob Forward's wiki entry on the Anthropic workbench and his introduction to APIs
Please explore our session two colab notebook
[THIS LINK HAS BEEN UPDATED TO LINK TO THE ACTUAL COLAB NOTEBOOK USED IN SESSION TWO. IF YOU COME ACROSS THIS LINK AND ARE NOT A MEMBER OF TEH AI-AND-HISTORY-COLLABORATAORY BUT WOULD LIKE ACCESS TO THE NOTEBOOK, CONTACT COLIN GREENSTREET, AUTHOR OF THE NOTEBOOK]
Come to our Tuesday session with lots of questions
If you have time, try using the Anthropic API from your own Colab notebook to some some historical research on your own use cases
0. Feedback since first session
Gavin Beinart-Smollan: prompts to correct raw HTR Yiddish
Maurice Brenner: narrative summarization: methodological issues
1. What is an API?
2. Introducting Google's Colab Notebook
3. Example: The UK National Archives's Discovery API
Geolocating and mapping metadata downloaded from the Discovery API
4. Example: The Anthropic API
Obtaining an API and inserting it into a Google Colab notebook
Running code for a prompt in a Google Colab notebook to perform a series of historical research functions
5. API keys for other large language models
6. Use case: Using an API to process and interrogate American Presidential rhetoric
7. Use case: Using an API to process and interrogate English High Court of Admiralty depositions
8. Discussion of use cases that other collaboratory members have, which may be suited to batch processing using the Anthropic API
The MarineLives project was founded in 2012. It is a volunteer lead collaboration dedicated to the transcription, enrichment and publication of English High Court of Admiralty depositions.
AI assistants and agents. Nov 19, 2024 talk
Analytical ontological summarization prompt
APIs and batch processing - second collaboratory session
APIs and batch processing ‐ learnings from second collaboratory session
Barbary pirate narrative summarization prompt
Barbary pirate deposition identification and narrative summarization prompt
Batch processing of raw HTR for clean up and summarization
Collaboratory members interests
Early Modern English Language Models
Fine-tuning - third oollaboratory session
History domain training data sets
Introduction to machine learning for historians
MarineLives and machine transcription
New skill set for historians? July 19, 2024 talk
Prompt engineering - first collaboratory session
Prompt engineering - learnings from first collaboratory session