Addestra il tuo Mini Language Model!
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Updated
Oct 1, 2025 - Jupyter Notebook
Addestra il tuo Mini Language Model!
A lightweight voice companion, optimized for macOS.
A set of reference implementations for various ML related tasks
Real-Time VLM Visual Analysis Web App
Kurtis is a fine-tuning, inference and evaluation tool built for SLMs (Small Language Models), such as Huggingface's SmolLM2.
A fine-tuned version of SmolLM2-360M-Instruct-bnb-4bit specialized for parsing unstructured calendar event requests into structured JSON data.
Active-inference Training with Learned Adaptive Stigmergy — Pure Rust AGI framework, 21 crates, 565 tests, 28 MCP tools, BF16 GPU inference (15.4 tok/s OLMo-3-7B on A100), OpenAI-compatible API, ZK proofs. Zero external dependencies.
NMOS (Neural Memory OS) is a predictive partial execution engine enabling 70B-level reasoning on 4GB VRAM. It uses the “Zero-Lag” hypothesis, leveraging typing latency as a compute window to mask memory limits via async layer prefetching and speculative decoding.
Systematically train and benchmark Mistral, Qwen2.5, and SmolLM2 on essay grading across 39 experiments through data analysis and engineering, structured preprocessing, instruction tuning, postprocessing, and leakage aware evaluation for robust score and rationale generation
Run SmolLM2 in a web browser with transformers.js
he point is not the model — the point is the pattern. Fork it, swap SmolLM2 for any model you want, and you have your own private LLM API running for free.
Build a system that analyzes resumes using NLP techniques, including preprocessing, skill extraction, and similarity scoring.
A lightweight, locally hosted LLM pipeline that extracts and normalizes unstructured student assignment text into a strict JSON schema using a fine-tuned SmolLM2-360M model served via Ollama.
ARIA is an AI-powered voice assistant that provides intelligent, web-enhanced answers to user queries. Built using a lightweight HuggingFace model, it integrates real-time web search and responds in a professional tone.
Adaptive tiny-model layer between LLMs and their tools — observes MCP traffic, trains per-tool LoRA compressors, synthesizes new tools from patterns.
Minimal Go implementation for inference Hugging Face SmolLM2 Instruct models.
A comprehensive toolkit for fine-tuning Large Language Models (LLMs) using cutting-edge techniques like LoRA, QLoRA, and Unsloth. Includes notebooks and scripts for customizing models such as SmolLM2, Llama-3.2, and Embedding Gemma for tasks like tool calling, reasoning, and embeddings. Perfect for researchers and developers looking to adapt LLMs
Free, open-source, privacy-focused, customizable AI chatbot.
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