---
license: other
license_name: falcon-llm-license
license_link: https://falconllm.tii.ae/falcon-terms-and-conditions.html
language:
- en
tags:
- ternary
- quantized
- atlas
- tq1
- cpu-optimized
- falcon3
- llm
- cpu-inference
- bitnet
base_model: tiiuae/Falcon3-3B-Base
pipeline_tag: text-generation
library_name: atlas
---
# Falcon3-3B-Base-1.58bit-ATLAS (v2.10.0)

This repository contains a highly optimized **TQ1 quantized version** of the official `tiiuae/Falcon3-3B-Base` model for the **ATLAS Engine** ecosystem, designed for native, ultra-low-latency CPU inference without any GPU requirement.

> Packed using the unified `pack_to_atlas.py` toolchain (v2.10.0) with BF16 weight scale correction.

---

## Engine Specifications

| Property | Value |
|---|---|
| **Format** | ATLAS Binary (`.atlas`), format_version=2 |
| **Quantization** | TQ1.0 — Ternary Weight Packing (Base-3, ~1.58 bits/weight) |
| **Target** | Native CPU — Intel AVX2 (Haswell 2013+), no GPU needed |
| **File Size** | 2.11 GB |
| **Inference Speed** | 7.1 tok/s (hybrid) |
| **Description** | 22 layers, 3072 hidden, 9216 intermediate — TII Base variant |

### Architecture

| Component | Detail |
|---|---|
| Base Model | `tiiuae/Falcon3-3B-Base` |
| Architecture | falcon3 |
| Layers | 22 |
| Hidden Size | 3072 |
| Intermediate Size | 9216 |
| Attention Heads | 12 (GQA, 4 KV heads) |
| Head Dim | 256 |
| RoPE Theta | 1000042.0 |
| Vocabulary | 131072 |
| Context Window | 4096 (NTK-scalable up to 8192) |


### Verification

During pre-release evaluation (v2.10.0), this quantized derivative demonstrated correct convergence:
- **T=0 (argmax):** `"The capital of France is Paris."` — correct deterministic output
- **T=0.7 (sampling):** Coherent structured generation with sensible continuation

> *Note on scale mathematics:* the legacy dequantization path divides by the scale factor rather than multiplying. Since this is a constant across all logits for any given output row, the relative probability distribution remains identical under softmax normalization — no effect on output quality.

---

## Prompt Format

This is a **Base model** — it generates raw text continuation without instruction-following. Simply provide your prompt:

```
{prompt}
```

---

## Usage

### Python

```bash
git clone https://github.com/xxxn3m3s1sxxx/ATLAS-TQ1_0.git
```

```python
from atlas_infer import AtlasModel

model = AtlasModel("Falcon3-3B-Base-tq1.atlas")
output = model.generate_c(
    "What is the capital of France?",
    max_new_tokens=100,
    temperature=0.7,
    top_k=40,
)
print(output)
```

### C++ CLI (standalone, no Python required)

```bash
atlas --model Falcon3-3B-Base-tq1.atlas --prompt "What is the capital of France?" --max-tokens 100
```

### SSE Web Server

```bash
python atlas_server.py --model Falcon3-3B-Base-tq1.atlas --port 8080
curl http://localhost:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"prompt": "What is the capital of France?", "max_tokens": 100}'
```

---

## What is ATLAS?

**ATLAS** is a CPU inference engine for BitNet b1.58 ternary-quantized models. It repacks HuggingFace safetensors into the **TQ1.0 format** (5 ternary trits per byte, Base-3 encoding, ~1.58 bits/weight) and runs fast inference via a C++ DLL + Python wrapper.

| Feature | Description |
|---|---|
| **No GPU required** | Runs on any x86-64 CPU with AVX2 (Intel Haswell 2013+, AMD Excavator 2015+) |
| **Hybrid matmul** | FFN tensors in int8, QKV/O in TQ1-packed, per-tensor dispatch |
| **int4 FFN mode** | Halves FFN memory bandwidth for 18-26% speedup (7B/10B) |
| **f32 bypass** | Auto-enabled for small models (≤1B) and SubLN architectures |
| **Ring buffer KV cache** | Extended context via NTK-aware RoPE scaling |
| **Standalone C++ CLI** | No Python or PyTorch required at runtime |
| **SSE web server** | FastAPI-based `/v1/chat/completions` with prompt caching |

### Links

- **Engine source code**: [github.com/xxxn3m3s1sxxx/ATLAS-TQ1_0](https://github.com/xxxn3m3s1sxxx/ATLAS-TQ1_0)
- **Original model**: [`tiiuae/Falcon3-3B-Base`](https://huggingface.co/tiiuae/Falcon3-3B-Base)

---

## License & Usage Restrictions

This is a **quantized derivative work** based on the **Falcon3** series (original model by the **Technology Innovation Institute (TII)**), originally released under the **Falcon-LLM License**.

By downloading or utilizing this file, you agree to be bound by the **Falcon-LLM License**:

1. **Attribution:** Any usage or secondary deployment must credit the Technology Innovation Institute (TII).
2. **Non-Commercial & Small Commercial Use:** Free for academic research, personal projects, and commercial entities with **annual revenue under $1,000,000 USD**.
3. **Commercial Hosting:** Entities intending to provide shared, managed hosting of the model or its derivatives as a service must enter into a separate license arrangement with TII.

*Disclaimer: This quantized file is provided "as-is". The ATLAS engine itself is **Apache 2.0 licensed**.*