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README.md

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+---
+base_model: KathirKs/phi-2_LogiCoT_finetuned
+inference: false
+model_creator: KathirKs
+model_name: phi-2_LogiCoT_finetuned
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+---
+# KathirKs/phi-2_LogiCoT_finetuned-GGUF
+
+Quantized GGUF model files for [phi-2_LogiCoT_finetuned](https://huggingface.co/KathirKs/phi-2_LogiCoT_finetuned) from [KathirKs](https://huggingface.co/KathirKs)
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [phi-2_logicot_finetuned.fp16.gguf](https://huggingface.co/afrideva/phi-2_LogiCoT_finetuned-GGUF/resolve/main/phi-2_logicot_finetuned.fp16.gguf) | fp16 | 5.56 GB  |
+| [phi-2_logicot_finetuned.q2_k.gguf](https://huggingface.co/afrideva/phi-2_LogiCoT_finetuned-GGUF/resolve/main/phi-2_logicot_finetuned.q2_k.gguf) | q2_k | 1.17 GB  |
+| [phi-2_logicot_finetuned.q3_k_m.gguf](https://huggingface.co/afrideva/phi-2_LogiCoT_finetuned-GGUF/resolve/main/phi-2_logicot_finetuned.q3_k_m.gguf) | q3_k_m | 1.48 GB  |
+| [phi-2_logicot_finetuned.q4_k_m.gguf](https://huggingface.co/afrideva/phi-2_LogiCoT_finetuned-GGUF/resolve/main/phi-2_logicot_finetuned.q4_k_m.gguf) | q4_k_m | 1.79 GB  |
+| [phi-2_logicot_finetuned.q5_k_m.gguf](https://huggingface.co/afrideva/phi-2_LogiCoT_finetuned-GGUF/resolve/main/phi-2_logicot_finetuned.q5_k_m.gguf) | q5_k_m | 2.07 GB  |
+| [phi-2_logicot_finetuned.q6_k.gguf](https://huggingface.co/afrideva/phi-2_LogiCoT_finetuned-GGUF/resolve/main/phi-2_logicot_finetuned.q6_k.gguf) | q6_k | 2.29 GB  |
+| [phi-2_logicot_finetuned.q8_0.gguf](https://huggingface.co/afrideva/phi-2_LogiCoT_finetuned-GGUF/resolve/main/phi-2_logicot_finetuned.q8_0.gguf) | q8_0 | 2.96 GB  |
+
+
+
+## Original Model Card:
+I am not the owner of this model's license. Please refer to the original model card for licensing information: [https://huggingface.co/microsoft/phi-2/blob/main/LICENSE]
+This model belongs to Microsoft Research.
+This is finetuned using just 500 samples LogiCoT (Chain of Thought) prompting dataset.