--- license: mit license_link: https://huggingface.co/microsoft/phi-4/resolve/main/LICENSE language: - en pipeline_tag: text-generation tags: - phi - nlp - math - code - chat - conversational - phi3 inference: parameters: temperature: 0 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 --- gguf/final version: https://huggingface.co/Pinkstack/PARM-V2-phi-4-16k-CoT-o1-gguf ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/QDHJhI0EVT_L9AHY_g3Br.png) [Phi-4 Technical Report](https://arxiv.org/pdf/2412.08905) 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** the model uses this prompt format: (modified phi-4 prompt) ``` {{ 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. ``` # 🧀 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:** ![example1](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/NoLJREYFU8LdMwynyLLMG.png) **example 2:** ![2](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/uboFipmS1ulfxeDgMBsBH.png) **example 3:** ![example2](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/c4h-nw0DPTrQgX-_tvBoT.png) **example 4:** ![example1part1.png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/Dcd6-wbpDQuXoulHaqATo.png) ![example1part2.png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/CoBYmYiRt9Z4IDFoOwHxc.png) All generated locally and pretty quickly too! 😲 Due to our very limited resources we weren't able to evaluate this model (yet..) if you evaluate it please do let us know! # 🧀 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 out flagship model, with top-tier reasoning, rivaling gemini-flash-exp-2.0-thinking and o1 mini. results are overall similar to both of them, we are not comparing to qwq as it has much longer results which waste tokens. # 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. # [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|