Graph Machine Learning
PEFT
Safetensors
English
Text-Graph-to-Text
chemistry
material science
molecular design
Instructions to use liuganghuggingface/Llamole-Qwen2-7B-Instruct-Adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use liuganghuggingface/Llamole-Qwen2-7B-Instruct-Adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "liuganghuggingface/Llamole-Qwen2-7B-Instruct-Adapter") - Notebooks
- Google Colab
- Kaggle
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Download README.md from liuganghuggingface/Llamole-Qwen2-7B-Instruct-Adapter: direct link, hf CLI and curl.
- Browser
- Download file 834 Bytes
-
https://huggingface.co/liuganghuggingface/Llamole-Qwen2-7B-Instruct-Adapter/resolve/main/README.md
- Command line
-
hf download hf://liuganghuggingface/Llamole-Qwen2-7B-Instruct-Adapter/README.md
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curl -L -o README.md https://huggingface.co/liuganghuggingface/Llamole-Qwen2-7B-Instruct-Adapter/resolve/main/README.md
834 Bytes
metadata
base_model: Qwen/Qwen2-7B-Instruct
tags:
- Text-Graph-to-Text
- chemistry
- material science
- molecular design
language:
- en
pipeline_tag: graph-ml
library_name: peft
datasets:
- liuganghuggingface/Llamole-MolQA
Model Card for Model ID
The adapter fine-tuned for Llamole (Multimodal Large Language Model for Molecular Discovery)
Model Sources [optional]
- Repository: https://github.com/liugangcode/Llamole
- Paper: Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
- Demo: Coming soon
Training Details
Coming soon