File size: 1,489 Bytes
96885ec e64ed1c 96885ec d2835ca 0e0d51f d2835ca |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 |
---
license: apache-2.0
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This model is optimized for Material Science by continuing pertaining on over 1 million Material science academic articles based on LLaMa-2-13b.
- **Developed by:** [UCSB]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [LLaMa-2]
- **Paper [optional]:** [https://arxiv.org/pdf/2401.01089.pdf]
- **Demo [optional]:** [More Information Needed]
## How to Get Started with the Model
```python
from transformers import LlamaTokenizer, LlamaForCausalLM
import torch
tokenizer = LlamaTokenizer.from_pretrained("Xianjun/Quokka-13b-base")
model = LlamaForCausalLM.from_pretrained("Xianjun/Quokka-13b-base").half().to("cuda")
instruction = "How to ..."
batch = tokenizer(instruction, return_tensors="pt", add_special_tokens=False).to("cuda")
with torch.no_grad():
output = model.generate(**batch, max_new_tokens=512, temperature=0.7, do_sample=True)
response = tokenizer.decode(output[0], skip_special_tokens=True)
```
## Citation
If you find Quokka useful in your research, please cite the following paper:
```latex
@inproceedings{Yang2024QuokkaAO,
title={Quokka: An Open-source Large Language Model ChatBot for Material Science},
author={Xianjun Yang and Stephen Wilson and Linda Ruth Petzold},
year={2024},
url={https://api.semanticscholar.org/CorpusID:266725577}
}
```
|