---
base_model: Pinkstack/Superthoughts-lite-1.8B-experimental-o1
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
- code
- superthoughts
- cot
- reasoning
- gguf
license: apache-2.0
language:
- en
pipeline_tag: text-generation
new_version: Pinkstack/Superthoughts-lite-v1-GGUF
---
![superthoughtslight.png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/2LuPB_ZPCGni3-PyCkL0-.png)

# Information
Advanced, high-quality and lite reasoning for a tiny size that you can run locally in Q8 on your phone! 😲

⚠️This is an experimental version: it may not always answer your question properly or correctly. currently reasoning may not always work on long conversations, as we've trained it on single turn conversations only.
SmolLM2-1.7B-Instruct on an advanced reasoning pattern dataset (half synthetic, half written manually by us.) to create this model. Supposed to output like this:
```
<|im_start|>user
What are you<|im_end|>
<|im_start|>assistant
<think>
Alright, the user just asked 'What are you', meaning they want to know who I am. I think my name is Superthoughts (lite version), created by Pinkstack on January 2025. I'm ready to answer their question.
</think>
Welcome! I'm Superthoughts (lite) created by Pinkstack in January 2025. Ready to help you with whatever you need!<|im_end|>
```
# Which quant is right for you?
- ***Q4_k_m:*** This quant *can* be used on most devices, quality is acceptable but reasoning quality is low.
- ***Q6_k:*** This quant is right in the middle, quality is better than q4_k_m but reasoning is still more limited than Q8.
- ***Q8_0:*** **RECOMMENDED** This quant yields very high quality results, good reasoning, good answers at a fast speed, on a Snapdragon 8 Gen 2 with 16 GB's of ram, it runs on 13 tokens per minute on average, see examples below.
- ***F16:*** Maximum quality GGUF quant, not needed for most tasks, results very similar to Q8_0.

# Examples:
all responses below generated with no system prompt, 400 maximum tokens and a temperature of 0.7 (not recommended, 0.3 - 0.5 is better):
Generated inside the android application, Pocketpal via GGUF Q8, using the model's prompt format.
1)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/wh33o-vjxIePfPqoN3q1z.png)
2)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/Y8optw73kTgqMnZKj3wKj.png)
3)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/6lywy3IYEIgzPnUIJ5RvF.png)
4)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/0K2rR9osmT20JrDvZuptV.png)

# Uploaded  model

- **Developed by:** Pinkstack
- **License:** apache-2.0
- **Finetuned from model :** HuggingFaceTB/SmolLM2-1.7B-Instruct

This smollm2 model was trained with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.