Instructions to use Rithaji-AI/Rithaji-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use Rithaji-AI/Rithaji-1.5B with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Rithaji-AI/Rithaji-1.5B to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Rithaji-AI/Rithaji-1.5B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Rithaji-AI/Rithaji-1.5B to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Rithaji-AI/Rithaji-1.5B", max_seq_length=2048, )
Rithaji-1.5B
Rithaji-1.5B is a custom fine-tuned language model optimized for conversational instruction-following and Python code generation. It was trained using the Unsloth library for high-efficiency memory management and faster fine-tuning.
Base Model
- Architecture: Qwen 2.5 (1.5B Parameters)
- License: Apache 2.0
Training Data & Legal Attribution
This model was fine-tuned using the following open-source datasets. We gratefully acknowledge the creators for making this data available to the open-source community:
- Databricks Dolly 15k: Utilized for general conversational tuning and instruction-following capabilities. Licensed under CC-BY-SA 3.0. Copyright (2023) Databricks, Inc.
- Google MBPP (Mostly Basic Python Problems): Utilized for Python code synthesis and logic formulation. Licensed under CC-BY 4.0. Created by Google Research.
Intended Use
This model is intended for developers, researchers, and hobbyists looking for a lightweight, locally hostable AI capable of writing Python functions and answering general queries. It can be run easily on consumer hardware using Transformers, vLLM, or natively via Ollama/LM Studio using the GGUF format.
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