Rishika70/Hack_To_Hire
This repository contains an analysis of different question answering models, including BERT, GPT-2, and T5. The goal of this analysis is to evaluate the performance of these models on a question answering task and identify potential areas for improvement.
No commits in the last 6 months.
Stars
—
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Aug 03, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/Rishika70/Hack_To_Hire"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
jpmorganchase/llm-email-spam-detection
LLM for Email Spam Detection
hppRC/llm-lora-classification
LLMとLoRAを用いたテキスト分類
makerlinck/AntLLM
A auto-classifier for files based on Langchain & Deepdanbooru-tagger-mini
Nightey3s/profanity-detection
A robust multimodal system for detecting and rephrasing profanity in both speech and text,...
byunsj/KoTox-Korean-Toxic-Instruction-Dataset
KoTox is an automatically generated instruction dataset in Korean. The instruction set is used...