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Model: prithivMLmods/SmolLM2-Math-IIO-1.7B-Instruct
Source: Original Platform

README.md

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+---
+license: creativeml-openrail-m
+datasets:
+- prithivMLmods/Math-IIO-68K-Mini
+language:
+- en
+base_model:
+- HuggingFaceTB/SmolLM2-1.7B-Instruct
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- safetensors
+- pytorch
+- llama
+- trl
+- ollama
+- llama-cpp
+- math
+- instruct
+---
+
+### SmolLM2-Math-IIO-1.7B-Instruct
+
+The **SmolLM2-Math-IIO-1.7B-Instruct** model is a fine-tuned variant of the **SmolLM2-1.7B** architecture, optimized for mathematical instruction and reasoning tasks. It is particularly suited for applications that require mathematical problem-solving, logical inference, and detailed step-by-step explanations.
+
+| File Name                              | Size       | Description                                    | Upload Status  |
+|----------------------------------------|------------|------------------------------------------------|----------------|
+| `.gitattributes`                       | 1.52 kB    | Git attributes configuration file              | Uploaded       |
+| `README.md`                            | 287 Bytes  | Updated README file                            | Updated        |
+| `config.json`                          | 940 Bytes  | Model configuration settings                   | Uploaded       |
+| `generation_config.json`               | 162 Bytes  | Generation-specific configurations             | Uploaded       |
+| `merges.txt`                           | 515 kB     | Merging information for tokenization           | Uploaded       |
+| `pytorch_model.bin`                    | 3.42 GB    | Full model weights (PyTorch format)            | Uploaded (LFS) |
+| `special_tokens_map.json`              | 572 Bytes  | Mapping for special tokens used by the model   | Uploaded       |
+| `tokenizer.json`                       | 3.77 MB    | Tokenizer configuration and vocabulary         | Uploaded       |
+| `tokenizer_config.json`                | 3.95 kB   | Tokenizer configuration for loading and usage  | Uploaded       |
+| `vocab.json`                           | 801 kB     | Vocabulary for the tokenizer                   | Uploaded       |
+
+### **Key Features:**
+
+1. **Math-Focused Capabilities:**  
+   This model is fine-tuned to handle a wide range of mathematical queries, from simple arithmetic to complex equations and mathematical proofs.  
+
+2. **Instruction-Tuned:**  
+   Specifically trained to follow structured queries and deliver clear, coherent outputs based on instructions, ensuring high-quality, relevant responses to prompts.
+
+3. **Tokenizer & Custom Tokens:**  
+   Includes a robust tokenizer configuration with support for mathematical notation, custom tokens, and an extended vocabulary for accurate understanding and output generation.
+
+---
+
+### **Training Details:**
+- **Base Model:** [SmolLM2-1.7B](https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct)  
+- **Dataset:** Trained on **Math-IIO-68K-Mini**, a dataset focused on mathematical instructions and logic-based queries, with a total of 68.8k examples.
+
+### **Capabilities:**
+- **Mathematical Problem-Solving:** Solves and explains complex mathematical problems, including algebra, calculus, and more advanced topics.  
+- **Instruction-Following:** Adheres to structured inputs and outputs, making it effective for generating step-by-step solutions.  
+- **Text Generation:** Capable of generating mathematical proofs, explanations, and educational content tailored to various user queries.
+
+---
+
+### **Usage Instructions:**
+1. **Model Setup:** Download all model files and ensure the PyTorch model weights and tokenizer configurations are included.  
+2. **Inference:** Load the model in a Python environment using frameworks like PyTorch or Hugging Face's Transformers.  
+3. **Customization:** Configure the model with the `config.json` and `generation_config.json` files for optimal performance during inference.
+
+---