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  - gguf-my-repo
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  ---
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- # Triangle104/Llama-3.2-1B-Instruct-Q8_0-GGUF
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  This model was converted to GGUF format from [`unsloth/Llama-3.2-1B-Instruct`](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct) 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/unsloth/Llama-3.2-1B-Instruct) for more details on the model.
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  Finetune Llama 3.2, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
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  Special Thanks
 
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  A huge thank you to the Meta and Llama team for creating and releasing these models.
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  Model Information
 
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  The Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks.
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  Model developer: Meta
 
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  - gguf-my-repo
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  ---
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+ # Triangle104/Unsloth_Llama-3.2-1B-Instruct-Q8_0-GGUF
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  This model was converted to GGUF format from [`unsloth/Llama-3.2-1B-Instruct`](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct) 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/unsloth/Llama-3.2-1B-Instruct) for more details on the model.
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  Finetune Llama 3.2, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
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  Special Thanks
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+ -
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  A huge thank you to the Meta and Llama team for creating and releasing these models.
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  Model Information
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+ -
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  The Meta Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. They outperform many of the available open source and closed chat models on common industry benchmarks.
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  Model developer: Meta