Terracotta – Platform for fine-tuning and evaluating LLMs

Hacker News

Terracotta is a free tool designed for fine-tuning and evaluating LLMs. We understand the challenges in experimenting with LLMs and have created a solution that streamlines the entire process, saving you valuable time and effort. Here are a few features that we have: 1. Training: Users can upload a dataset and fine-tune different LLMs provided by OpenAI within minutes using our training dashboard. 2. Qualitative evaluation: A playground for qualitatively comparing base models vs. fine-tuned models from OpenAI and Cohere. 3. Quantitative evaluation: An evaluation tool that lets you run inference on a dataset with any model with a few clicks, and compare several models across different metrics of your choice. We calculate relevant metrics depending on what kind of task you want to do.

Visit product View on Hacker NewsJul 17, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, models · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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