metadata

base_model: unsloth/gemma-3-4b-it-unsloth-bnb-4bit
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - gemma3
license: apache-2.0
language:
  - en

🚀 Fine-tuned Gemma 3 Model (4B, 4-bit) by Webkul

This repository contains a fine-tuned version of Unsloth's gemma-3-4b-it model, optimized for lightweight 4-bit inference and instruction tuning using Hugging Face's TRL and Unsloth's speed-optimized framework.

🔧 Model Details

Base Model: unsloth/gemma-3-4b-it-unsloth-bnb-4bit
Fine-tuned By: Webkul
License: Apache 2.0
Language: English (en)
Model Size: 4B parameters (4-bit quantized)
Frameworks Used: Unsloth, Hugging Face Transformers, TRL

📚 Fine-tuning Dataset

This model was fine-tuned on unopim dev documentation available at https://devdocs.unopim.com/, focusing on structured software documentation and developer support content.

💡 Intended Use

Conversational AI assistants trained on UnoPIM developer docs
API documentation question answering
Developer tools and chatbot integrations
Contextual helpdesk or onboarding bots for UnoPIM products

🧪 How to Use

You can use this model with the Hugging Face transformers library:

from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "webkul/gemma-3-4b-it-unopim-docs"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

input_text = "How do I integrate the UnoPIM API for product syncing?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=300)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

📄 License This model is licensed under the Apache License 2.0.