pszemraj

"""
inference_openai.py - text generation with OpenAI API

    See https://platform.openai.com/docs/quickstart for more details.

Usage:
python inference_openai.py --prompt "The quick brown fox jumps over the lazy dog." --model "gpt-3.5-turbo" --temperature 0.5 --max_tokens 256 --n 1 --stop "."

Detailed usage:
python inference_openai.py --help

pszemraj

LLM Foundry Configuration Reference

This document provides a comprehensive reference for all configuration options available in LLM Foundry YAML files. Configuration files are used for training, fine-tuning, and evaluating large language models.

Table of Contents

• Configuration Format Types
• Variables
• Model Configuration
• MPT Model Options

pszemraj

"""
util script for loading, basic processing, converting reddit posts -> hf dataset

https://arctic-shift.photon-reddit.com/download-tool
"""
import pandas as pd
from datasets import Dataset, load_dataset

src = "./r_LocalLLaMA_posts.jsonl" # update with relevant path
df = pd.read_json(src, lines=True).convert_dtypes()

pszemraj

# -*- coding: utf-8 -*-
"""gemma-3n-test

pip install -U -q git+https://github.com/huggingface/transformers.git
pip install -U -q git+https://github.com/huggingface/pytorch-image-models.git
"""

from transformers import pipeline
import torch

pszemraj

#!/usr/bin/env python3
"""
Slice a (possibly very tall) image into fixed-height chunks.

Creates a sibling directory called  <image stem>_slices/
and writes   slice_000.png, slice_001.png, …  inside it.
"""

import argparse
from pathlib import Path

pszemraj

"""
Create & save an hf dataset with train/test/val splits from dir w/ text files

Ideal structure:

    root / section_name_1 / file 1
    root / section_name_1 / file 2
    root / section_name_1 / file YYY
    root / section_name_2 / file 1
    root / section_name_2 / file ZZZ

pszemraj

from dataclasses import dataclass
from typing import List, Optional, Tuple

import torch
import torch.nn as nn


@dataclass
class _LayerSummary:
    """A dataclass to hold summary information for a single layer."""

pszemraj

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Standalone Asynchronous Nanonets-OCR-s Inference Script using vLLM and PyMuPDF.

This script processes PDF files from an input directory using the
nanonets/Nanonets-OCR-s model served locally by vLLM via its OpenAI-compatible API.
It renders each page, sends API requests concurrently for OCR, extracts the
structured markdown/HTML text, and saves the combined text for each PDF into a
corresponding .txt file in the specified output directory.

pszemraj

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Standalone Asynchronous RolmOCR Inference Script using vLLM and PyMuPDF.

This script processes PDF files from an input directory using the
reducto/RolmOCR model served locally by vLLM via its OpenAI-compatible API.
It renders each page, sends API requests concurrently for OCR, extracts plain
text, and saves the combined text for each PDF into a corresponding .txt file
in the specified output directory.

pszemraj

"""
WaveNet: An Ultra-Small Language Model (PyTorch Implementation)

Based on the paper: https://arxiv.org/abs/2411.02674
Hugging Face Transformers compatible implementation.
"""
import math
from typing import Dict, Optional, Tuple, Union

import torch