Instructions to use Hamzajutt17/60540 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Hamzajutt17/60540 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Hamzajutt17/60540") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
metadata
license: afl-3.0
datasets:
- >-
Manusagents/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
language:
- en
metrics:
- google_bleu
base_model:
- google/gemma-4-12B-it
new_version: chatqaq/Qwen3.6-27B-Claude-Mythos-Distilled-MTP-GGUF
library_name: sentence-transformers
tags:
- agent
AI Study Assistant
A professional AI Study Assistant built using Google Gemini, Python and Gradio.
Features
- AI Chat
- Explain Any Topic
- Notes Summarizer
- MCQ Generator
- Quiz Generator
- Assignment Generator
- Grammar Checker
- Translator
- Study Planner
Technologies
- Python
- Google Gemini API
- Gradio
- Hugging Face Spaces
Deployment
Create a Hugging Face Space using Gradio.
Upload:
- app.py
- requirements.txt
- README.md
Go to
Settings → Variables and Secrets
Create
GEMINI_API_KEY
Paste your Gemini API key.
The application will automatically deploy.
Author
Muhammad Hamza