86 lines
1.6 KiB
Markdown
86 lines
1.6 KiB
Markdown
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---
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license: apache-2.0
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base_model: DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- merge
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- programming
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- code generation
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- code
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- coding
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- coder
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- chat
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- brainstorm
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- qwen
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- qwen3
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- qwencoder
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- brainstorm20x
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- esper
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- esper-3
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- valiant
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- valiant-labs
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- qwen-3
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- qwen-3-14b
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- 14b
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- reasoning
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- code-instruct
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- python
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- javascript
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- dev-ops
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- jenkins
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- terraform
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- scripting
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- powershell
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- azure
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- aws
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- gcp
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- cloud
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- problem-solving
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- architect
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- engineer
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- developer
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- creative
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- analytical
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- expert
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- rationality
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- conversational
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- instruct
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- float32
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- mlx
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datasets:
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- sequelbox/Titanium2.1-DeepSeek-R1
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- sequelbox/Tachibana2-DeepSeek-R1
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- sequelbox/Raiden-DeepSeek-R1
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library_name: mlx
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---
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# Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-mlx
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This model [Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-mlx](https://huggingface.co/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-mlx) was
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converted to MLX format from [DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x](https://huggingface.co/DavidAU/Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x)
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using mlx-lm version **0.26.0**.
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("Qwen3-Esper3-Reasoning-CODER-Instruct-21B-Brainstorm20x-bf16-mlx")
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prompt = "hello"
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if tokenizer.chat_template is not None:
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messages = [{"role": "user", "content": prompt}]
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prompt = tokenizer.apply_chat_template(
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messages, add_generation_prompt=True
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)
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response = generate(model, tokenizer, prompt=prompt, verbose=True)
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```
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