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@@ -22,7 +22,7 @@ quantized_by: alvarobartt
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  # Model Card for LINCE-ZERO-7B-GGUF
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- [LINCE-ZERO]https://huggingface.co/clibrain/lince-zero) is a fine-tuned LLM for instruction following of [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b). The team/org leading the fine-tune is [Clibrain](https://huggingface.co/clibrain), and the datasets used are both [Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca) and [Dolly](https://huggingface.co/datasets/databricks/databricks-dolly-15k) datasets, both translated into Spanish and augmented to 80k examples (as Clibrain claims in its [model card](https://huggingface.co/clibrain/lince-zero#model-card-for-lince-zero)).
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  This model contains the quantized variants using the GGUF format, introduced by the [llama.cpp](https://github.com/ggerganov/llama.cpp) team.
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  ### Model Description
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  - **Model type:** Falcon
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- - **Finetuned from model:** [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b)
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  - **Created by**: [TIIUAE](https://huggingface.co/tiiuae)
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  - **Fine-tuned by:** [Clibrain](https://huggingface.co/clibrain)
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  - **Quantized by:** [alvarobartt](https://huggingface.co/alvarobartt)
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  | [lince-zero-7b-q4_k_m.gguf](https://huggingface.co/alvarobartt/lince-zero-7b-GGUF/blob/main/lince-zero-7b-q4_k_m.gguf) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
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  | [lince-zero-7b-q5_k_s.gguf](https://huggingface.co/alvarobartt/lince-zero-7b-GGUF/blob/main/lince-zero-7b-q5_k_s.gguf) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
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  | [lince-zero-7b-q5_k_m.gguf](https://huggingface.co/alvarobartt/lince-zero-7b-GGUF/blob/main/lince-zero-7b-q5_k_m.gguf) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
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- **Note*
 
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  ## Uses
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  # Model Card for LINCE-ZERO-7B-GGUF
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+ [LINCE-ZERO](https://huggingface.co/clibrain/lince-zero) is a fine-tuned LLM for instruction following of [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b). The team/org leading the fine-tune is [Clibrain](https://huggingface.co/clibrain), and the datasets used are both [Alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca) and [Dolly](https://huggingface.co/datasets/databricks/databricks-dolly-15k) datasets, both translated into Spanish and augmented to 80k examples (as Clibrain claims in its [model card](https://huggingface.co/clibrain/lince-zero#model-card-for-lince-zero)).
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  This model contains the quantized variants using the GGUF format, introduced by the [llama.cpp](https://github.com/ggerganov/llama.cpp) team.
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  ### Model Description
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  - **Model type:** Falcon
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+ - **Fine-tuned from model:** [Falcon 7B](https://huggingface.co/tiiuae/falcon-7b)
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  - **Created by**: [TIIUAE](https://huggingface.co/tiiuae)
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  - **Fine-tuned by:** [Clibrain](https://huggingface.co/clibrain)
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  - **Quantized by:** [alvarobartt](https://huggingface.co/alvarobartt)
 
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  | [lince-zero-7b-q4_k_m.gguf](https://huggingface.co/alvarobartt/lince-zero-7b-GGUF/blob/main/lince-zero-7b-q4_k_m.gguf) | Q4_K_M | 4 | 7.87 GB| 10.37 GB | medium, balanced quality - recommended |
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  | [lince-zero-7b-q5_k_s.gguf](https://huggingface.co/alvarobartt/lince-zero-7b-GGUF/blob/main/lince-zero-7b-q5_k_s.gguf) | Q5_K_S | 5 | 8.97 GB| 11.47 GB | large, low quality loss - recommended |
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  | [lince-zero-7b-q5_k_m.gguf](https://huggingface.co/alvarobartt/lince-zero-7b-GGUF/blob/main/lince-zero-7b-q5_k_m.gguf) | Q5_K_M | 5 | 9.23 GB| 11.73 GB | large, very low quality loss - recommended |
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+
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+ **Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
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  ## Uses
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