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Model: Pinkstack/PARM-Qwen2.5-o1-0.5B-GGUF
Source: Original Platform

README.md

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+---
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- gguf
+- reasoning
+- Qwen2
+- Qwen
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+---
+
+![BY_PINKSTACK.png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/2xMulpuSlZ3C1vpGgsAYi.png)
+
+[PRAM V2](https://huggingface.co/collections/Pinkstackorg/pram-v2-67612d3c542b9121bf15891c)
+
+# 🧀 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 reasoning training parameters so it would have similar outputs to qwen QwQ (only much, smaller.), We trained with [this](https://huggingface.co/datasets/gghfez/QwQ-LongCoT-130K-cleaned) dataset.
+it is designed to run on any device, from your phone to high-end PC. that is why we've included a BF16 quant.
+
+
+To use this model, you must use a service which supports the GGUF file format.
+Additionaly, this is the Prompt Template, it uses the qwen2 template.
+```
+{{{ if .System }}<|system|>
+{{ .System }}<|im_end|>
+{{ end }}{{ if .Prompt }}<|user|>
+{{ .Prompt }}<|im_end|>
+{{ end }}<|assistant|>
+{{ .Response }}<|im_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 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)