Science
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This is a Phi-1_5 model trained on camel-ai/physics. This model is for research purposes only and should not be used in production settings.
Find below some example scripts on how to use the model in transformers
:
from huggingface_hub import notebook_login
from datasets import load_dataset, Dataset
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
model = "ArtifactAI/phi-physics"
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 are the common techniques used in identifying a new species, and how can scientists accurately categorize it within the existing taxonomy system?")
The model was trained on camel-ai/phi-physics, a dataset of question/answer pairs.
The following bitsandbytes
quantization config was used during training:
The following bitsandbytes
quantization config was used during training:
@misc{phi-math,
title={phi-physics},
author={Matthew Kenney},
year={2023}
}