96 lines
1.7 KiB
Markdown
96 lines
1.7 KiB
Markdown
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---
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language:
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- en
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library_name: mlx
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pipeline_tag: text-generation
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tags:
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- shining-valiant
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- shining-valiant-3
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- valiant
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- valiant-labs
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- qwen
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- qwen-3
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- qwen-3-1.7b
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- 1.7b
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- reasoning
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- code
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- code-reasoning
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- science
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- science-reasoning
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- physics
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- biology
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- chemistry
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- earth-science
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- astronomy
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- machine-learning
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- artificial-intelligence
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- compsci
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- computer-science
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- information-theory
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- ML-Ops
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- math
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- cuda
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- deep-learning
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- transformers
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- agentic
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- LLM
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- neuromorphic
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- self-improvement
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- complex-systems
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- cognition
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- linguistics
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- philosophy
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- logic
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- epistemology
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- simulation
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- game-theory
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- knowledge-management
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- creativity
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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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- chat
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- instruct
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- mlx
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base_model: ValiantLabs/Qwen3-1.7B-ShiningValiant3
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datasets:
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- sequelbox/Celestia3-DeepSeek-R1-0528
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- sequelbox/Mitakihara-DeepSeek-R1-0528
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- sequelbox/Raiden-DeepSeek-R1
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license: apache-2.0
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---
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# Qwen3-1.7B-ShiningValiant3-bf16-mlx
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This model [Qwen3-1.7B-ShiningValiant3-bf16-mlx](https://huggingface.co/Qwen3-1.7B-ShiningValiant3-bf16-mlx) was
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converted to MLX format from [ValiantLabs/Qwen3-1.7B-ShiningValiant3](https://huggingface.co/ValiantLabs/Qwen3-1.7B-ShiningValiant3)
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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("Qwen3-1.7B-ShiningValiant3-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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