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@@ -10,6 +10,46 @@ base_model: AGI-0/Art-v0-3B
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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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+ -
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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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+
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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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+
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+ Recommendations
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+
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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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+
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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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+
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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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+ ---
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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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