mseri

function HorizontalRule(el)
  return pandoc.RawBlock('tex', '\\newpage')
end

mseri

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "transformers>=5.0.0rc1",
#     "mlx-audio==0.3.0rc1",
#     "click",
#     "numpy",
#     "soundfile",
#     "sounddevice",
# ]

mseri

The following instructions refer to gemma-3-1b-it-qat-q4_0 and Ubuntu Linux 24.04.3 LTS but can be applied to other Gemma 3 IT QAT checkpoints as well.

0. Prerequisites

To quantize the original safetensors snapshot, we need llama.cpp and a few helper tools that can be obtained together with llama.cpp. To make sure we are on the latest version, we first clone and build the newest version of llama.cpp.

sudo apt-get install -y --no-install-recommends \

mseri

Textbooks in Mathematics

A list of links to useful mathematical textbooks available for free on the Internet. They are all legal and maintained by their authors or by the legitimate publisher.

All the documents are in English. They are in a printable format - Postscript or Adobe Portable Document Format. You are free to download, read and print them. Here are some links to other sites offering lists of free mathematical textbooks.

For any comments, please, contact me: alex_stef@yahoo.com

mseri

# train_grpo.py
#
# See https://github.com/willccbb/verifiers for ongoing developments
#
"""
citation:

@misc{brown2025grpodemo,
  title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
  author={Brown, William},

mseri

#!/bin/bash
set -euo pipefail

MODELS="aquif, gemma3, granite4, granite4-moe, lfm2, lfm2-moe, lfm2-vl, ministral3 (3,8B;i,r), nemotron, qwen3(i,r), voxtral"

function usage() {
  echo "Usage: $0 <model> [options]"
  echo "Models: $MODELS."
  echo "Options:"
  echo "  --dry to see the invocation string only"

mseri

Let's hack on llm!

If you have uv installed (and you should!), you can install llm globally in a uv-managed tool environment with:

uv tool install llm

If you want to use models other than OpenAI models, you'll need some extensions:

mseri

#!/usr/bin/swift
// Started from the code in https://terminalbytes.com/iphone-8-solar-powered-vision-ocr-server/
// Edited from Mistral generated code: https://chat.mistral.ai/chat/563cacdf-6def-49e4-9df6-ee8e263978c5
import AppKit
import CoreGraphics
import Foundation
import SwiftUI
import Vision

func processImageSync(imagePath: String) -> String? {

mseri

import sys
from io import StringIO

import streamlit as st              # pip install streamlit
from code_editor import code_editor # pip install streamlit_code_editor
import ollama as ol                 # pip install ollama

st.set_page_config(layout='wide')
st.title('`Offline code completion`')

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"""
A minimal, fast example generating text with Llama 3.1 in MLX.

To run, install the requirements:

    pip install -U mlx transformers fire

Then generate text with:

    python l3min.py "How tall is K2?"