metadata
license: apache-2.0
language:
- en
pipeline_tag: summarization
widget:
- text: What is the peak phase of T-eV?
example_title: Question Answering
tags:
- arxiv
Table of Contents
TL;DR
This is a Phi-1_5 model trained on camel-ai/chemistry. This model is for research purposes only and should not be used in production settings.
Model Description
- Model type: Language model
- Language(s) (NLP): English
- License: Apache 2.0
- Related Models: Phi-1_5
Usage
Find below some example scripts on how to use the model in transformers:
Using the Pytorch model
from huggingface_hub import notebook_login
from datasets import load_dataset, Dataset
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
model = "ArtifactAI/phi-chemistry"
model = AutoModelForCausalLM.from_pretrained(base_model, trust_remote_code= True)
tokenizer = AutoTokenizer.from_pretrained(base_model, trust_remote_code=True)
def generate(prompt):
inputs = tokenizer(f'''Below is an instruction that describes a task. Write a response that appropriately completes the request If you are adding additional white spaces, stop writing".\n\n### Instruction:\n{prompt}.\n\n### Response:\n ''', return_tensors="pt", return_attention_mask=False)
streamer = TextStreamer(tokenizer, skip_prompt= True)
_ = model.generate(**inputs, streamer=streamer, max_new_tokens=500)
generate("What is the IUPAC name for the organic compound with the molecular formula C6H12O2?")
Training Data
The model was trained on camel-ai/chemistry, a dataset of question/answer pairs. Questions are generated using the t5-base model, while the answers are generated using the GPT-3.5-turbo model.
Citation
@misc{phi-chemistry,
title={phi-chemistry},
author={Matthew Kenney},
year={2023}
}