Instructions to use sleepy-panda21/Llama_fine_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sleepy-panda21/Llama_fine_tuned with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use sleepy-panda21/Llama_fine_tuned 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 sleepy-panda21/Llama_fine_tuned 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 sleepy-panda21/Llama_fine_tuned to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sleepy-panda21/Llama_fine_tuned to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="sleepy-panda21/Llama_fine_tuned", max_seq_length=2048, )
Fine-Tuned AI Counseling Assistant
This repository contains the LoRA adapter weights fine-tuned on top of Qwen2.5-7B-Instruct.
Model Description
This model has been specifically fine-tuned to act as a supportive, empathetic, and non-judgmental conversational assistant. It focuses on validating emotions, processing stress or academic overwhelm, and maintaining supportive therapeutic pacing.
- Trained with: Unsloth & PEFT
- Framework: QLoRA (4-bit quantization)
- Language: English
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