masani/SFT_gsm8k_Llama-3.2-3B_epoch_1_global_step_29
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:May 14, 2025Architecture:Transformer Warm
The masani/SFT_gsm8k_Llama-3.2-3B_epoch_1_global_step_29 is a 3.2 billion parameter language model with a 32768 token context length. This model is fine-tuned for specific tasks, indicated by its SFT (Supervised Fine-Tuning) and gsm8k (GSM8K dataset) designation. It is likely optimized for mathematical reasoning and problem-solving, particularly on grade school math word problems.
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Model Overview
This model, masani/SFT_gsm8k_Llama-3.2-3B_epoch_1_global_step_29, is a 3.2 billion parameter language model with a substantial context length of 32768 tokens. It has undergone Supervised Fine-Tuning (SFT) specifically on the GSM8K dataset, which focuses on grade school mathematical reasoning problems.
Key Characteristics
- Parameter Count: 3.2 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a long context window of 32768 tokens, beneficial for complex problem-solving or multi-turn interactions.
- Fine-tuned for GSM8K: Optimized for tasks related to mathematical reasoning, particularly grade school math word problems.
Potential Use Cases
- Mathematical Problem Solving: Ideal for applications requiring the model to understand and solve arithmetic and word problems.
- Educational Tools: Can be integrated into platforms for tutoring or generating math exercises.
- Reasoning Tasks: Suitable for scenarios where logical deduction and numerical understanding are critical.