---
license: apache-2.0
base_model: DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-128k-ctx
language:
- en
pipeline_tag: text-generation
tags:
- merge
- programming
- code generation
- code
- coding
- coder
- chat
- brainstorm
- qwen
- qwen3
- qwencoder
- brainstorm20x
- esper
- esper-3
- valiant
- valiant-labs
- qwen-3
- qwen-3-14b
- 14b
- reasoning
- code-instruct
- python
- javascript
- dev-ops
- jenkins
- terraform
- scripting
- powershell
- azure
- aws
- gcp
- cloud
- problem-solving
- architect
- engineer
- developer
- creative
- analytical
- expert
- rationality
- conversational
- instruct
- float32
- mlx
datasets:
- sequelbox/Titanium2.1-DeepSeek-R1
- sequelbox/Tachibana2-DeepSeek-R1
- sequelbox/Raiden-DeepSeek-R1
library_name: mlx
---

# Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-128k-ctx-q6-mlx

This model [Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-128k-ctx-q6-mlx](https://huggingface.co/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-128k-ctx-q6-mlx) was
converted to MLX format from [DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-128k-ctx](https://huggingface.co/DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-128k-ctx)
using mlx-lm version **0.26.3**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-128k-ctx-q6-mlx")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```