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README.md
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This model was converted to GGUF format from [`AGI-0/Art-v0-3B`](https://huggingface.co/AGI-0/Art-v0-3B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/AGI-0/Art-v0-3B) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`AGI-0/Art-v0-3B`](https://huggingface.co/AGI-0/Art-v0-3B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/AGI-0/Art-v0-3B) for more details on the model.
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---
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Model details:
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Auto Regressive Thinker (Art) v0 3B
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Art v0 3B is our inaugural model in the Art series, fine-tuned from Qwen/Qwen2.5-3B-Instruct using a specialized dataset generated with Gemini 2.0 Flash Thinking. Read more about the Art series
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Model Details
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Base Model: Qwen2.5-3B-Instruct
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Architecture: Transformer
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Size: 3B parameters
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Usage
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The model incorporates a reasoning mechanism using specific tags:
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<|start_reasoning|> model's reasoning process <|end_reasoning|> model's response
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Recommendations
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Use the model without quantization
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Use the tokenizer chat template
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Use a low temperature 0.1-0.3 and repetition_penalty of 1.1
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Training Details
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This experimental model was trained on a curated dataset generated using Gemini 2.0 Flash Thinking. Detailed training methodology, dataset, and code are available exclusively to our community members.
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About Us
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We are a community-funded AI research lab focused on advancing open-source AGI development. Our community members support us through Patreon donations.
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Community Access
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Our supporters get exclusive access to:
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Training dataset
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Training code and methodology
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Behind-the-scenes development insights
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Future model previews
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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