Instructions to use Eeshan082004/quotedesk-student with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Eeshan082004/quotedesk-student with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-270m-it") model = PeftModel.from_pretrained(base_model, "Eeshan082004/quotedesk-student") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from Eeshan082004/quotedesk-student: direct link, hf CLI and curl.
- Browser
- Download file 548 Bytes
-
https://huggingface.co/Eeshan082004/quotedesk-student/resolve/main/README.md
- Command line
-
hf download hf://Eeshan082004/quotedesk-student/README.md
-
curl -L -o README.md https://huggingface.co/Eeshan082004/quotedesk-student/resolve/main/README.md
548 Bytes
| base_model: google/gemma-3-270m-it | |
| library_name: peft | |
| license: gemma | |
| tags: [quotedesk, lora, extraction, synthetic-data] | |
| # QuoteDesk student v1 | |
| LoRA adapter for Gemma 3 270M that extracts structured quote requests from messy customer emails | |
| (fictional company, synthetic data). Trained with Unsloth; eval results in `eval.json`. | |
| Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms. | |
| Use of this adapter is subject to the Gemma Prohibited Use Policy (ai.google.dev/gemma/prohibited_use_policy). | |