109 lines
3.0 KiB
Markdown
109 lines
3.0 KiB
Markdown
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---
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library_name: transformers
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tags:
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- math
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- lora
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- science
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- chemistry
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- biology
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- code
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- text-generation-inference
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- unsloth
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- llama
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license: apache-2.0
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datasets:
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- HuggingFaceTB/smoltalk
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language:
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- en
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- de
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- es
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- fr
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- it
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- pt
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- hi
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- th
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base_model:
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- meta-llama/Llama-3.2-1B-Instruct
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---
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You can use ChatML & Alpaca format.
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You can chat with the model via this [space](https://huggingface.co/spaces/suayptalha/Chat-with-FastLlama).
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**Overview:**
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FastLlama is a highly optimized version of the Llama-3.2-1B-Instruct model. Designed for superior performance in constrained environments, it combines speed, compactness, and high accuracy. This version has been fine-tuned using the MetaMathQA-50k section of the HuggingFaceTB/smoltalk dataset to enhance its mathematical reasoning and problem-solving abilities.
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**Features:**
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Lightweight and Fast: Optimized to deliver Llama-class capabilities with reduced computational overhead.
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Fine-Tuned for Math Reasoning: Utilizes MetaMathQA-50k for better handling of complex mathematical problems and logical reasoning tasks.
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Instruction-Tuned: Pre-trained on instruction-following tasks, making it robust in understanding and executing detailed queries.
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Versatile Use Cases: Suitable for educational tools, tutoring systems, or any application requiring mathematical reasoning.
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**Performance Highlights:**
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Smaller Footprint: The model delivers comparable results to larger counterparts while operating efficiently on smaller hardware.
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Enhanced Accuracy: Demonstrates improved performance on mathematical QA benchmarks.
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Instruction Adherence: Retains high fidelity in understanding and following user instructions, even for complex queries.
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**Loading the Model:**
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```py
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import torch
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from transformers import pipeline
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model_id = "suayptalha/FastLlama-3.2-1B-Instruct"
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pipe = pipeline(
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"text-generation",
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model=model_id,
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "You are a friendly assistant named FastLlama."},
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{"role": "user", "content": "Who are you?"},
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]
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outputs = pipe(
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messages,
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max_new_tokens=256,
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)
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print(outputs[0]["generated_text"][-1])
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```
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**Dataset:**
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Dataset: MetaMathQA-50k
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The MetaMathQA-50k subset of HuggingFaceTB/smoltalk was selected for fine-tuning due to its focus on mathematical reasoning, multi-step problem-solving, and logical inference. The dataset includes:
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Algebraic problems
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Geometric reasoning tasks
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Statistical and probabilistic questions
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Logical deduction problems
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**Model Fine-Tuning:**
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Fine-tuning was conducted using the following configuration:
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Learning Rate: 2e-4
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Epochs: 1
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Optimizer: AdamW
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Framework: Unsloth
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**License:**
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This model is licensed under the Apache 2.0 License. See the LICENSE file for details.
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<a href="https://www.buymeacoffee.com/suayptalha" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>
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