|
|
|
|
|
!pip install git+https://github.com/huggingface/transformers.git |
|
|
!pip install sentencepiece |
|
|
!pip install peft |
|
|
!pip install accelerate |
|
|
!pip install bitsandbytes |
|
|
import torch |
|
|
from peft import PeftModel |
|
|
import transformers |
|
|
|
|
|
from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig |
|
|
|
|
|
tokenizer = LlamaTokenizer.from_pretrained("decapoda-research/llama-7b-hf") |
|
|
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") |
|
|
print(device) |
|
|
model = LlamaForCausalLM.from_pretrained( |
|
|
"decapoda-research/llama-7b-hf", |
|
|
load_in_8bit=True, |
|
|
torch_dtype=torch.float16, |
|
|
device_map="auto", |
|
|
offload_folder = "." |
|
|
) |
|
|
|
|
|
model = PeftModel.from_pretrained( |
|
|
model, |
|
|
"tloen/alpaca-lora-7b", |
|
|
torch_dtype=torch.float16, |
|
|
device_map="auto", |
|
|
load_in_8bit = True, |
|
|
offload_folder="." |
|
|
) |
|
|
|
|
|
def generate_prompt(instruction, input=None): |
|
|
if input: |
|
|
return f"""Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
|
|
|
|
|
### Instruction: |
|
|
{instruction} |
|
|
|
|
|
### Input: |
|
|
{input} |
|
|
|
|
|
### Response:""" |
|
|
else: |
|
|
return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request. |
|
|
|
|
|
### Instruction: |
|
|
{instruction} |
|
|
|
|
|
### Response:""" |
|
|
|
|
|
|
|
|
model.eval() |
|
|
|
|
|
|
|
|
def evaluate( |
|
|
instruction, |
|
|
input=None, |
|
|
temperature=0.1, |
|
|
top_p=0.75, |
|
|
top_k=40, |
|
|
num_beams=4, |
|
|
**kwargs, |
|
|
): |
|
|
prompt = generate_prompt(instruction, input) |
|
|
inputs = tokenizer(prompt, return_tensors="pt") |
|
|
input_ids = inputs["input_ids"].to(device) |
|
|
generation_config = GenerationConfig( |
|
|
temperature=temperature, |
|
|
top_p=top_p, |
|
|
top_k=top_k, |
|
|
num_beams=num_beams, |
|
|
**kwargs, |
|
|
) |
|
|
with torch.no_grad(): |
|
|
generation_output = model.generate( |
|
|
input_ids=input_ids, |
|
|
generation_config=generation_config, |
|
|
return_dict_in_generate=True, |
|
|
output_scores=True, |
|
|
max_new_tokens=2048, |
|
|
) |
|
|
s = generation_output.sequences[0] |
|
|
output = tokenizer.decode(s) |
|
|
return output.split("### Response:")[1].strip() |
|
|
input = """RESEARCH REPORT NO. 1037027Final Clinical Study Report -NV25118: A Randomized, Multicentre, Single Blinded, Parallel Study of the Safety of 100 mg and 200 mg Oseltamivir Administered Intravenously for the Treatment of Influenza in Patients Aged > 13 Years. Report No. 1037027. June 3, 2013 Study Sponsor(s):Dr F Hoffman La-Roche LtdStudy Dates:First patient screened: Jan 15, 2010 Last patient visit: Sept 14, 2012Trial Phase:II/IIIIndication:InfluenzaName of Principal Investigator Thomas MathewSponsor's Signatory: Personnel Responsible for Clinical and Statistical Analyses: Clinical analysis:John ThomasSafety analysis:William RichardStatistical analysis:Charles DanielPharmacokinetic analysis:Robert DavidGCP Compliance: This study was conducted in accordance with the principles of GCP""" |
|
|
instruction = "Extract Names, Diseases, Dates from below text:" |
|
|
|
|
|
print("Response:", evaluate(instruction,input)) |
