Instructions to use sulcan/CHATQCD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sulcan/CHATQCD with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "sulcan/CHATQCD") - Notebooks
- Google Colab
- Kaggle
| base_model: unsloth/llama-3-8b-Instruct-bnb-4bit | |
| library_name: peft | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| https://github.com/sulcantonin/CHATQCD_ICHEP24 | |
| ## Model Details | |
| ### Model Description | |
| <!-- Provide a longer summary of what this model is. --> | |
| - **Developed by:** Antonin Sulc, Patrick L.S. Connor | |
| - **Model type:** [More Information Needed] | |
| - **Language(s) (NLP):** English | |
| - **Finetuned from model [optional]:** unsloth/llama-3-8b-Instruct-bnb-4bit | |
| ### Model Sources [optional] | |
| <!-- Provide the basic links for the model. --> | |
| - **Repository:** https://github.com/sulcantonin/CHATQCD_ICHEP24 | |
| - **Paper:** [TBD] | |
| - PEFT 0.12.0 |