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--- |
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base_model: EpistemeAI/metatune-gpt20b-R1.1 |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- gpt_oss |
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- mlx |
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license: apache-2.0 |
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language: |
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- en |
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datasets: |
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- EpistemeAI/recursive_self_improvement_dataset |
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library_name: mlx |
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pipeline_tag: text-generation |
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--- |
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# metatune-gpt20b-R1.1-qx86-hi-mlx |
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Metrics aren't everything. The qx86-hi is more fun than q8-hi. Enjoy the quant. |
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Sample output: |
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```bash |
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┌───────────────────────┐ ┌───────────────┐ ┌──────────────┐ |
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│ UI / CLI │<------>| Agent |<-------->| Provider │ |
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└───────────────────────┘ ├───────────────┤ └──────────────┘ |
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│ Thread work │ |
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│ HTTP, FILE, │ |
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│ TOOL, etc. │ |
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└───────┬───────┘ |
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│ DB logging (SQLite) |
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▼ |
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┌───────────────────────┐ |
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│ SQLite LOG DB │ |
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└───────────────────────┘ |
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┌───────────────────────────────┐ |
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│ PostgreSQL (orchestrator) │ |
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└───────────────────────────────┘ |
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+---------------------------+ +--------------------------+ |
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| PL/Perl functions | | Tables & triggers | |
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+---------------------------+ +--------------------------+ |
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``` |
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It's really hard to line up ASCII code, but looked good on screen |
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This model [metatune-gpt20b-R1.1-qx86-hi-mlx](https://huggingface.co/nightmedia/metatune-gpt20b-R1.1-qx86-hi-mlx) was |
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converted to MLX format from [EpistemeAI/metatune-gpt20b-R1.1](https://huggingface.co/EpistemeAI/metatune-gpt20b-R1.1) |
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using mlx-lm version **0.28.4**. |
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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("metatune-gpt20b-R1.1-qx86-hi-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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