Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-mlx/README.md

license, base_model, language, pipeline_tag, tags, datasets, library_name

license	base_model	language	pipeline_tag	tags	datasets	library_name
apache-2.0	DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x	en	text-generation	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	sequelbox/Titanium2.1-DeepSeek-R1 sequelbox/Tachibana2-DeepSeek-R1 sequelbox/Raiden-DeepSeek-R1	mlx

Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-mlx

This model Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-mlx was converted to MLX format from DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x using mlx-lm version 0.26.0.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-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)