---
tags:
  - gguf
  - llama.cpp
  - llama-cpp
  - unsloth
  - text-generation
  - transformers
  - qwen2
  - agentic-workflows
  - tool-calling
license: apache-2.0
language:
  - en
base_model: orangejuicesmith/Mythos-Nano-safetensor
---

# TB-X — Mythos Nano GGUF

**TB-X** is a GGUF conversion of [Mythos Nano](https://huggingface.co/orangejuicesmith/Mythos-Nano-safetensor), prepared using [Unsloth](https://github.com/unslothai/unsloth) and made compatible with the [llama.cpp](https://github.com/ggml-org/llama.cpp) inference ecosystem.

The repository provides multiple GGUF precision and quantization variants, allowing users to choose an appropriate balance between model size, memory usage, inference performance, and output quality.

## Model Information

| Property | Details |
|---|---|
| Repository | `Shadow0482/tb-x` |
| Model name | TB-X |
| Base model | `orangejuicesmith/Mythos-Nano-safetensor` |
| Architecture tag | Qwen2 |
| Format | GGUF |
| Conversion | Unsloth |
| Inference engine | llama.cpp |
| Language | English |
| License | Apache 2.0 |

## Development & Agent Workflow

TB-X was developed with a teacher-guided, tool-driven agent workflow.

The development process used:

- **Claude Opus 5.5** — Teacher model.
- **GPT-6 Astra** — Teacher and reasoning support.
- **Tool orchestration** — Tool calls and agent interactions used throughout the workflow.

The workflow involved approximately **500 million tool-call and agent-flow interactions**.

This figure describes the reported development workflow activity; it does not represent the model's parameter count, training tokens, or number of training samples.

> The teacher models were used as part of the development workflow. They are not inference dependencies of the released GGUF files.

## Available Model Files

TB-X includes the following GGUF variants:

| File | Precision / Quantization |
|---|---|
| `Mythos-Nano-safetensor.BF16.gguf` | BF16 |
| `Mythos-Nano-safetensor.F16.gguf` | F16 |
| `Mythos-Nano-safetensor.Q2_K_L.gguf` | Q2_K_L |
| `Mythos-Nano-safetensor.Q3_K_M.gguf` | Q3_K_M |
| `Mythos-Nano-safetensor.Q4_0.gguf` | Q4_0 |
| `Mythos-Nano-safetensor.Q4_1.gguf` | Q4_1 |
| `Mythos-Nano-safetensor.Q4_K_M.gguf` | Q4_K_M |
| `Mythos-Nano-safetensor.Q5_K_M.gguf` | Q5_K_M |
| `Mythos-Nano-safetensor.Q6_K.gguf` | Q6_K |
| `Mythos-Nano-safetensor.Q8_0.gguf` | Q8_0 |

### Choosing a Quantization

- **BF16 / F16:** Higher precision, with greater memory requirements.
- **Q8_0:** High-quality quantized option.
- **Q6_K / Q5_K_M:** Good options when prioritizing quality with reduced memory usage.
- **Q4_K_M / Q4_0 / Q4_1:** Practical lower-memory options.
- **Q3_K_M / Q2_K_L:** More aggressive compression for constrained hardware.

Actual memory requirements depend on the architecture, context length, runtime, and inference configuration.

## Usage with llama.cpp

Install or build a recent version of [llama.cpp](https://github.com/ggml-org/llama.cpp).

### 1. Text Generation

Run TB-X using the Hugging Face model repository:

```bash
llama-cli -hf Shadow0482/tb-x --jinja
```

### 2. Chat Template

The `--jinja` option enables llama.cpp's Jinja chat-template handling.

This is useful when the model repository provides a compatible chat template.

### 3. Run a Local GGUF File

Download your preferred quantization and run it directly:

```bash
llama-cli \
  -m Mythos-Nano-safetensor.Q4_K_M.gguf \
  --jinja \
  -cnv
```

Replace the filename with your selected GGUF variant.

### 4. OpenAI-Compatible API Server

Start a local inference server:

```bash
llama-server \
  -hf Shadow0482/tb-x \
  --jinja \
  --host 0.0.0.0 \
  --port 8080
```

The API is available at:

```text
http://localhost:8080/v1
```

You can connect compatible applications and clients to the local server.

## Compatibility

TB-X is designed for use with the llama.cpp ecosystem.

- llama-cli
- llama-server
- OpenAI-compatible API clients
- Compatible GGUF applications

Tool calling and agent functionality depend on the model's capabilities, chat template, and the runtime's tool-calling implementation. A GGUF conversion alone does not guarantee native function-calling support.

## Credits & Acknowledgements

- **Base model:** [orangejuicesmith/Mythos-Nano-safetensor](https://huggingface.co/orangejuicesmith/Mythos-Nano-safetensor)
- **Conversion framework:** [Unsloth](https://github.com/unslothai/unsloth)
- **Inference engine:** [llama.cpp](https://github.com/ggml-org/llama.cpp)
- **Teacher models:** Claude Opus 5.5 and GPT-6 Astra

## License

The base model metadata specifies the Apache 2.0 license. Please review the base model's license and applicable conditions before redistributing or using derivative artifacts.