---
title: OpenLLM Inference Space
emoji: 🚀
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.1
app_file: app.py
pinned: false
license: gpl-3.0
---

# 🚀 OpenLLM Inference Space

Welcome to the OpenLLM Inference Space! This is a comprehensive interface for running inference on our trained OpenLLM models with customizable parameters.

## 🎯 Available Models

We provide **7 different models** trained for varying numbers of steps:

| Model | Training Steps | Description | Best Loss |
|-------|---------------|-------------|-----------|
| **4k Model** | 4,000 | Early training stage, basic language patterns | ~6.2 |
| **6k Model** | 6,000 | Improved coherence, better vocabulary usage | ~5.8 |
| **7k Model** | 7,000 | Enhanced text generation quality | ~5.5 |
| **8k Model** | 8,000 | More sophisticated language understanding | ~5.3 |
| **9k Model** | 9,000 | Best performing model (latest training) | ~5.2 |
| **10k Model** | 10,000 | Latest extended training, maximum performance | ~5.22 |
| **10k Improved** | 10,000 | Improved training process, proper checkpoint format | ~5.1774 |

## 🎮 How to Use

1. **Select a Model** from the dropdown menu
2. **Load the Model** to see its information
3. **Enter Your Prompt** in the text box
4. **Adjust Parameters** (temperature, max length, etc.)
5. **Generate Text** and see the results!

## ⚙️ Parameters

- **Temperature**: Controls randomness (0.1-2.0)
- **Max Length**: Number of tokens to generate (10-500)
- **Top-K**: Limits to top-k most likely tokens (1-100)
- **Top-P**: Nucleus sampling threshold (0.1-1.0)

## 🧠 Model Architecture

- **Model Size**: Small (35.8M parameters)
- **Layers**: 6 transformer layers
- **Embedding**: 512 dimensions
- **Vocabulary**: 32,000 tokens (SentencePiece)
- **Context Length**: 1,024 tokens

---

**OpenLLM Inference Space** - Experience the power of open-source language models! 🚀