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README.md

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 license: cc-by-nc-4.0
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+
+# Model Card for Envoid_Mixtral-Instruct-ITR-8x7B-GGUF
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+Envoid_Mixtral-Instruct-ITR-8x7B quantized with love. 
+
+Starting out with Q4_K_M, future plans for imatrix IQ quants.
+
+Original model card below for reference.
+
+---
+license: cc-by-nc-4.0
+---
+# Caution this model may be unpredictable
+![](https://files.catbox.moe/y8nv86.jpg)
+## Mixtral-Instruct-ITR (Interpolative Training Regression)
+
+We have to go back, edition. 
+
+For this model I took what I learned in the making of [Cat-8x7B](https://huggingface.co/Envoid/Cat-8x7B) and went back to the very beginning and SLERP merged [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) onto [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1)
+
+While the results aren't perfect the model feels more creative and less overcooked than Mixtral Instruct is often accused of being. 
+
+The hopes are that this should also have left the model much more receptive to additional finetuning and I am interested to see what comes of it so please feel free to download it and have fun. 
+
+Apologies about the small shard size (keep forgetting to change the mergekit config back)
+
+## The model is a lot less likely to refuse certain requests in this state:
+
+so if you are going to apply additional finetuning to the model you may need to bolster its alignment depending on your use case. 
+
+The model still responds well to [INST] Thingie [/INST] formatting quite well. 
+
+Or if preferred this can easily be reproduced if you have both base and instruct models handy using mergekit (mixtral branch) with the following config
+```
+models:
+  - model: ./mistralai_Mixtral-8x7B-Instruct-v0.1
+  - model: ./mistralai_Mixtral-8x7B-v0.1
+merge_method: slerp
+base_model: ./mistralai_Mixtral-8x7B-v0.1
+parameters:
+  t:
+    - value: 0.5
+dtype: float16
+```