Instructions to use adithyn/qwen3-14b-cvpr-chat-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adithyn/qwen3-14b-cvpr-chat-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("adithyn/qwen3-14b-cvpr-chat-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use adithyn/qwen3-14b-cvpr-chat-lora 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 adithyn/qwen3-14b-cvpr-chat-lora 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 adithyn/qwen3-14b-cvpr-chat-lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for adithyn/qwen3-14b-cvpr-chat-lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="adithyn/qwen3-14b-cvpr-chat-lora", max_seq_length=2048, )
Uploaded model
- Developed by: adithyn
- Version: 2.0 (trained for 540 steps/3 epochs)
- License: apache-2.0
- Finetuned from model : unsloth/qwen3-14b-unsloth-bnb-4bit
- Observation: Model seemed to have generalized but since dataset contained short answers model only returns short direct answers.
This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.
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