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

.gitattributes

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+unsloth.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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Modelfile

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+
+FROM /kaggle/working/Pinkstack/PARM-Qwen2.5-o.1-0.5B-GGUF/unsloth.F16.gguf
+TEMPLATE """{{- if .Messages }}
+{{- if or .System .Tools }}<|im_start|>system
+{{- if .System }}
+{{ .System }}
+{{- end }}
+{{- if .Tools }}
+
+# Tools
+
+You may call one or more functions to assist with the user query.
+
+You are provided with function signatures within <tools></tools> XML tags:
+<tools>
+{{- range .Tools }}
+{"type": "function", "function": {{ .Function }}}
+{{- end }}
+</tools>
+
+For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
+<tool_call>
+{"name": <function-name>, "arguments": <args-json-object>}
+</tool_call>
+{{- end }}<|im_end|>
+{{ end }}
+{{- range $i, $_ := .Messages }}
+{{- $last := eq (len (slice $.Messages $i)) 1 -}}
+{{- if eq .Role "user" }}<|im_start|>user
+{{ .Content }}<|im_end|>
+{{ else if eq .Role "assistant" }}<|im_start|>assistant
+{{ if .Content }}{{ .Content }}
+{{- else if .ToolCalls }}<tool_call>
+{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
+{{ end }}</tool_call>
+{{- end }}{{ if not $last }}<|im_end|>
+{{ end }}
+{{- else if eq .Role "tool" }}<|im_start|>user
+<tool_response>
+{{ .Content }}
+</tool_response><|im_end|>
+{{ end }}
+{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant
+{{ end }}
+{{- end }}
+{{- else }}
+{{- if .System }}<|im_start|>system
+{{ .System }}<|im_end|>
+{{ end }}{{ if .Prompt }}<|im_start|>user
+{{ .Prompt }}<|im_end|>
+{{ end }}<|im_start|>assistant
+{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}"""
+PARAMETER stop "<|im_end|>"
+PARAMETER stop "<|endoftext|>"
+PARAMETER temperature 1.5
+PARAMETER min_p 0.1

PARM-Qwen2.5-0.5B-o.1-BF16.gguf

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+size 994156384

PARM-Qwen2.5-0.5B-o.1-Q4_K_M.gguf

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PARM-Qwen2.5-0.5B-o.1-Q6_K.gguf

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PARM-Qwen2.5-0.5B-o.1-Q8_0.gguf

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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)

config.json

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+{
+    "model_type": "qwen2"
+}