Gemma_finetuned_april_24_2025

Gemma-3-12B Firecrawl Expert

This is a fine-tuned version of Gemma-3-12B specialized in answering questions about Firecrawl web scraping.

Model Details

• Base Model: unsloth/gemma-3-12b-it
• Fine-tuning Method: LoRA (Low-Rank Adaptation) using Unsloth
• Training Library: Unsloth
• Fine-tuned: April 24, 2025

Training Data

The model was fine-tuned on the bexgboost/openai-agents-python-qa-firecrawl dataset, which contains question-answer pairs about Firecrawl and web scraping techniques.

Use Cases

This model is specialized in:

• Answering questions about Firecrawl web scraping
• Providing guidance on web scraping techniques
• Helping with Firecrawl implementation

Training Parameters

• LoRA Rank: 8
• LoRA Alpha: 8
• Learning Rate: 2e-4
• Epochs: 1
• Quantization: 4-bit

Usage with Unsloth

from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name = "Laksh99/Gemma_finetuned_april_24_2025",
    max_seq_length = 2048,
    load_in_4bit = True
)