|
--- |
|
library_name: transformers |
|
license: llama3.2 |
|
language: |
|
- en |
|
base_model: |
|
- meta-llama/Llama-3.2-1B-Instruct |
|
pipeline_tag: text-generation |
|
tags: |
|
- code |
|
- math |
|
- cot |
|
- conversational |
|
- moe |
|
- Superthoughts |
|
--- |
|
## ⚠️THIS MODEL IS EXPERIMENTAL!! Full release soon! |
|
|
|
 |
|
After more than two months since the release of superthoughts lite v1, we finally release the new version. **v2** |
|
Unlike the first generation of superthoughts lite, this model is a MoE (Mixture of experts), of 4 special fine-tuned experts based off of llama-3.2-1B models. |
|
# Information |
|
- In GGUF Q8_0, the model runs at ~8 tokens per second on a Snapdragon 8 Gen 2 with 12GB of ram, which is faster than Pinkstack/PARM-V2-QwQ-Qwen-2.5-o1-3B-GGUF (which runs at ~5 tokens a second). |
|
- The chat expert was fine tuned on 23 different languages for 2 epochs, but the model should still only be used for english-to-english generation. |
|
|
|
- This model has a total of 3.91B parameters, and 2 experts are active with each token. There is an expert for math, code, general conversations and medical situations. |
|
- Long context: the model supports up to **131,072** input tokens, and can generate up to **16,384** tokens. |
|
- Unhinged at times: As this is an experimental version, it is extremly sensitive to prompts, so it is incredibly unhindged someties. please use a tempature of around or at 0.85. |
|
- To enable proper reasoning, set this as the system prompt: |
|
``` |
|
You are Superthoughts lite v2 by Pinkstack, which thinks before answering user questions. always respond in the following format:\n<think>\n(Your thinking process\n</think>\n(Your final output). |
|
``` |
|
And or start the model output with a ```<think>``` xml tag. ideally do both. |
|
⚠️ Due to the nature of an experimental model, it may fall into reasoning loops, it was trained on SFT only and GRPO/RL was not yet done, so we list it as experimental. |
|
users are responsible for all outputs from this model. |
|
This experimental model is more of a proof-of-concept for now. It fully works and it has some pretty nice performance, for having less than 2 billion parameters activated per token. |
|
|
|
# Examples |
|
Note, on our local test, it runs at about 55 tokens a second. |
|
 |
|
|
|
 |
|
|
|
|
|
 |
|
**If you have any questions, feel free to open a "New Discussion".** |
|
|
|
Fine tuning was done using Unsloth, MoE was created using MergeKit. |
