suayptalha
/

FastLlama-3.2-LoRA

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 ---
 library_name: transformers
 tags:
 - unsloth
 ---
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 ---
 library_name: transformers
 tags:
+- math
+- lora
+- science
+- chemistry
+- biology
+- code
+- text-generation-inference
 - unsloth
+license: apache-2.0
+datasets:
+- HuggingFaceTB/smoltalk
+language:
+- en
+base_model:
+- meta-llama/Llama-3.2-1B-Instruct
 ---
+![FastLlama-Logo](FastLlama.png)
+These are only LoRA adapters of
+You can use ChatML & Alpaca format.
+**Overview:**
+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.
+**Features:**
+Lightweight and Fast: Optimized to deliver Llama-class capabilities with reduced computational overhead.
+Fine-Tuned for Math Reasoning: Utilizes MetaMathQA-50k for better handling of complex mathematical problems and logical reasoning tasks.
+Instruction-Tuned: Pre-trained on instruction-following tasks, making it robust in understanding and executing detailed queries.
+Versatile Use Cases: Suitable for educational tools, tutoring systems, or any application requiring mathematical reasoning.
+**Performance Highlights:**
+Smaller Footprint: The model delivers comparable results to larger counterparts while operating efficiently on smaller hardware.
+Enhanced Accuracy: Demonstrates improved performance on mathematical QA benchmarks.
+Instruction Adherence: Retains high fidelity in understanding and following user instructions, even for complex queries.
+**Loading the Model:**
+```py
+import torch
+from transformers import pipeline
+model_id = "suayptalha/FastLlama-3.2-1B-Instruct"
+pipe = pipeline(
+    "text-generation",
+    model=model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+messages = [
+    {"role": "system", "content": "You are a friendly assistant named FastLlama."},
+    {"role": "user", "content": "Who are you?"},
+]
+outputs = pipe(
+    messages,
+    max_new_tokens=256,
+)
+print(outputs[0]["generated_text"][-1])
+```
+**Dataset:**
+Dataset: MetaMathQA-50k
+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:
+Algebraic problems
+Geometric reasoning tasks
+Statistical and probabilistic questions
+Logical deduction problems
+**Model Fine-Tuning:**
+Fine-tuning was conducted using the following configuration:
+Learning Rate: 2e-4
+Epochs: 1
+Optimizer: AdamW
+Framework: Unsloth
+**License:**
+This model is licensed under the Apache 2.0 License. See the LICENSE file for details.