Update README.md


README.md

@@ -1,22 +1,53 @@
 ---
-base_model: unsloth/qwen2.5-0.5b-instruct-bnb-4bit
 tags:
 - text-generation-inference
 - transformers
 - unsloth
-- qwen2
 - gguf
+- reasoning
+- Qwen2
+- Qwen
 license: apache-2.0
 language:
 - en
+pipeline_tag: text-generation
 ---
 
-# Uploaded  model
+![BY_PINKSTACK.png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/2xMulpuSlZ3C1vpGgsAYi.png)
 
+# 🧀 Which quant is right for you? 
+
+- ***Q4:*** This model should be used for super low end devices like older phones or older laptops due to its very compact size, quality is okay but fully usable. 
+- ***Q6:*** This model should be used on most modern devices, good quality and very quick responses. 
+- ***Q8:*** This model should be used on most modern devices Responses are very high quality, but its a little slower than q6
+- ***BF16:*** This Lossless model should only be used if maximum quality is needed; it doesn't perform well speed wise, but text results are high quality.
+
+## Things you should be aware of when using PARM models (Pinkstack Accuracy Reasoning Models) 🧀
+
+This PARM is based on Qwen 2.5 0.5B which has gotten extra training parameters so it would have similar outputs to O.1 Mini, We trained with [this](https://huggingface.co/datasets/gghfez/QwQ-LongCoT-130K-cleaned) dataset.
+
+To use this model, you must use a service which supports the GGUF file format.
+Additionaly, this is the Prompt Template, it uses the Phi-3 template.
+```
+{{ if .System }}<|system|>
+{{ .System }}<|end|>
+{{ end }}{{ if .Prompt }}<|user|>
+{{ .Prompt }}<|end|>
+{{ end }}<|assistant|>
+{{ .Response }}<|end|>
+```
+
+Or if you are using an anti prompt: <|end|><|assistant|> 
+
+Highly recommended to use with a system prompt. 
+
+# Extra information
 - **Developed by:** Pinkstack
 - **License:** apache-2.0
 - **Finetuned from model :** unsloth/qwen2.5-0.5b-instruct-bnb-4bit
 
-This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+This model was trained using [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+Used this model? Don't forget to leave a like :)
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)