Instructions to use Agaba-Embedded4/Deepfund_medical_assitant_vLLM_lora_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Agaba-Embedded4/Deepfund_medical_assitant_vLLM_lora_model2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Agaba-Embedded4/Deepfund_medical_assitant_vLLM_lora_model2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded model
- Developed by: Agaba-Embedded4
- License: apache-2.0
- Finetuned from model : Agaba-Embedded4/MedConnect-Cintinually-Pre-trained-Mistral-7B
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
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