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---
license: mit
license_link: https://huggingface.co/microsoft/phi-4/resolve/main/LICENSE
language:
- en
- multilingual
pipeline_tag: text-generation
tags:
- phi
- nlp
- math
- code
- chat
- conversational
- phi3
- reasoning
- CoT
inference:
parameters:
temperature: 0.3
widget:
- messages:
- role: user
content: How many R's in strawberry? Think step by step.
library_name: transformers
datasets:
- amphora/QwQ-LongCoT-130K
base_model:
- microsoft/phi-4
model-index:
- name: SuperThoughts-CoT-14B-16k-o1-QwQ
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 5.15
name: averaged accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Pinkstack%2FSuperThoughts-CoT-14B-16k-o1-QwQ
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 52.85
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Pinkstack%2FSuperThoughts-CoT-14B-16k-o1-QwQ
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 40.79
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Pinkstack%2FSuperThoughts-CoT-14B-16k-o1-QwQ
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 19.02
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Pinkstack%2FSuperThoughts-CoT-14B-16k-o1-QwQ
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 21.79
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Pinkstack%2FSuperThoughts-CoT-14B-16k-o1-QwQ
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 47.43
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=Pinkstack%2FSuperThoughts-CoT-14B-16k-o1-QwQ
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Llmexplorer lmsys elo
type: elo-score
config: main
split: test
metrics:
- type: elo
value: 1203
name: elo
source:
url: https://llm.extractum.io/list/?benchmark=score_elo
name: LLMexplorer lmsys elo score
---
Renamed to parm-2
Please note, the low IFEVAL results is due to this model always reasoning, instruction following is limited, which caused it to have very low ifeval results, this should not matter for most use cases.
gguf/final version: https://huggingface.co/Pinkstack/PARM-V2-phi-4-16k-CoT-o1-gguf
This model can be merged with phi-4 based LLMs!
[Phi-4 Technical Report](https://arxiv.org/pdf/2412.08905)
[superthoughts 14B openllm detailed results](https://huggingface.co/datasets/open-llm-leaderboard/Pinkstack__SuperThoughts-CoT-14B-16k-o1-QwQ-details)
Phi-4 that has been tuned to be more advanced at reasoning.
Unlike other Parm models we had to optimize our fine tuning process to ensure accuracy while still being able to release this model. **Training loss: 0.443800**
Beats qwen/qwq at MATH & MuSR & GPQA (MuSR being a reasoning benchmark)
Evaluation:
the model can use this prompt format: (modified phi-4 prompt, by adding a system prompt telling the model to reason before responding you'll get a similar if not better response)
```
{{ if .System }}<|system|>
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|user|>
{{ .Prompt }}<|im_end|>
{{ end }}<|assistant|>{{ .CoT }}<|CoT|>
{{ .Response }}<|FinalAnswer|><|im_end|>
```
It is recommended to use a system prompt like this one:
```
You are a helpful ai assistant. Make sure to put your finalanswer at the end.
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/Pinkstack__SuperThoughts-CoT-14B-16k-o1-QwQ-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=Pinkstack%2FSuperThoughts-CoT-14B-16k-o1-QwQ&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
| Metric |Value (%)|
|-------------------|--------:|
|**Average** | 31.17|
|IFEval (0-Shot) | 5.15|
|BBH (3-Shot) | 52.85|
|MATH Lvl 5 (4-Shot)| 40.79|
|GPQA (0-shot) | 19.02|
|MuSR (0-shot) | 21.79|
|MMLU-PRO (5-shot) | 47.43|
# other leaderboard
According to https://llm.extractum.io/list/?benchmark=score_elo, this model is in the top 20 on their LMSys ELO score leaderboard.
# 🧀 Examples:
(q4_k_m, 10GB rtx 3080, 64GB memory, running inside of MSTY, all use "You are a friendly ai assistant." as the System prompt.)
**example 1:**
**example 2:**
**example 3:**
**example 4:**
All generated locally
# 🧀 Information
- ⚠️ A low temperature must be used to ensure it won't fail at reasoning. we use 0.3 - 0.8!
- ⚠️ Due to the current prompt format, it may sometimes put <|FinalAnswer|> without providing a final answer at the end, you can ignore this or modify the prompt format.
This is our flagship model, with top-tier reasoning, rivaling gemini-flash-exp-2.0-thinking and o1 mini. Overall, the results are similar to both of them.
# Uploaded model
- **Developed by:** Pinkstack
- **License:** MIT
- **Finetuned from model :** microsoft/phi-4
This phi-4 model was trained with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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