AlexIoannides/llm-regression
Exploring the classical regression capabilities of LLMs.
This tool helps data scientists and machine learning engineers explore using large language models (LLMs) to solve classical regression problems. You provide your training data (features and target values), and it uses an LLM to learn the relationship. The output is a model that can predict new target values based on unseen features, offering an alternative approach to traditional regression methods.
No commits in the last 6 months.
Use this if you are a data scientist or researcher interested in experimenting with LLMs for numerical prediction tasks, leveraging their language understanding for regression.
Not ideal if you need highly interpretable models, strict control over traditional statistical assumptions, or are working with extremely large datasets where LLM inference costs and latency might be prohibitive.
Stars
18
Forks
1
Language
Python
License
MIT
Category
Last pushed
May 20, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/AlexIoannides/llm-regression"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related models
snsn3/policy-LLM
Finetuning an LLM for heavy policy work
richardsonlima/synapsense
SynapSense: Python In-Context Learning for Large Language Models SynapSense is a cutting-edge...
dhargopala/xplain
Python Library to compute the XPLAIN score for LLM expainability.
G-B-KEVIN-ARJUN/size-precision-slm-bench
is it better to run a Tiny Model (2B-4B) at High Precision (FP16/INT8), or a Large Model (8B+)...
MyriamBA/LLM_use_cases
A simple collection of LLM apps powered by HuggingFace.