Text Generation
PEFT
Safetensors
English
insurance
actuarial
life-insurance
health-insurance
accounting
cpa
cfa
legal
bar-exam
finance
wealth-management
estate-planning
mistral
lora
qlora
conversational
Eval Results (legacy)
Instructions to use h3ir/morbi-v022-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use h3ir/morbi-v022-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-Small-Instruct-2409") model = PeftModel.from_pretrained(base_model, "h3ir/morbi-v022-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0f6bb6363ed473541682844bb45d1b8a0139b51657dc61bca0d6f80c3231d3c
- Size of remote file:
- 5.24 kB
- SHA256:
- 1ae190295e48cab3b922071e38120142d80dfcab8e6e90b55d3e850fe4d7ecf1
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