初始化项目，由ModelHub XC社区提供模型

Model: harsh762011/numinao14-new
Source: Original Platform

README.md

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+---
+license: cc-by-nc-3.0
+base_model: unsloth/phi-4-mini-reasoning
+tags:
+  - text-generation-inference
+  - transformers
+  - unsloth
+  - phi-4
+language:
+  - en
+---
+
+# Phi-4 Mini Reasoning – JEE Mathematics Finetuned Model
+
+A new version of the model present at `harsh762011/numiano14`.
+
+# Uploaded Finetuned Model
+
+- **Developed by:** Harsh Srivastava
+- **License:** cc-by-nc-3.0
+- **Finetuned from model:** unsloth/phi-4-mini-reasoning
+
+This Phi-4 model was trained faster using Unsloth and Hugging Face TRL.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+
+---
+
+# Description
+
+This model is a finetuned version of Phi-4 Mini Reasoning designed for solving JEE-level mathematics problems.
+
+The model is optimized for:
+- Step-by-step mathematical reasoning
+- Symbolic problem solving
+- Competitive exam-style question solving
+
+---
+
+# Training Dataset
+
+Total samples used: 500k+ filtered mathematics and reasoning samples.
+
+The training pipeline focuses on JEE-level mathematical difficulty using keyword-based dataset filtering.
+
+## Sources
+
+- AI-MO/NuminaMath-CoT — 293k samples (2 epochs)
+- AI-MO/NuminaMath-TIR — 68,850 samples
+- MetaMathQA — 70k samples
+- TIGER-Lab MathInstruct — 125,220 samples
+- PhysicsWallahAI JEE Main 2025 (Jan) — 182 samples
+- PhysicsWallahAI JEE Main 2025 (Apr) — 169 samples
+- MMLU High School Mathematics — 78 samples
+- MMLU College Mathematics — 50 samples
+- MMLU Abstract Algebra — 25 samples
+
+---
+
+# Training Details
+
+- **Base model:** Phi-4 Mini Reasoning
+- **Framework:** Unsloth + Hugging Face TRL
+- **Training method:** LoRA finetuning
+- **Sequence length:** 2048
+- **Optimizer:** AdamW 8bit
+
+---
+
+# Intended Purpose
+
+The model is designed for:
+
+- JEE mathematics reasoning
+- Step-by-step mathematical explanations
+- Competitive exam problem solving
+- Mathematical chain-of-thought reasoning
+
+---
+
+# Limitations
+
+- The model may still generate incorrect mathematical reasoning.
+- Outputs should be verified for high-stakes usage.
+- The model is still under active improvement and continued training.