sfttrainer()

Curious Corncrake answered on August 23, 2023 Popularity 1/10 Helpfulness 1/10

answer sfttrainer()

sfttrainer()

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from transformers import AutoModelForCausalLM, AutoTokenizer
from datasets import load_dataset
from trl import SFTTrainer, DataCollatorForCompletionOnlyLM

dataset = load_dataset("lucasmccabe-lmi/CodeAlpaca-20k", split="train")

model = AutoModelForCausalLM.from_pretrained("facebook/opt-350m")
tokenizer = AutoTokenizer.from_pretrained("facebook/opt-350m")

def formatting_prompts_func(example):
    output_texts = []
    for i in range(len(example['instruction'])):
        text = f"### Question: {example['instruction'][i]}\n ### Answer: {example['output'][i]}"
        output_texts.append(text)
    return output_texts

response_template = " ### Answer:"
collator = DataCollatorForCompletionOnlyLM(response_template, tokenizer=tokenizer)

trainer = SFTTrainer(
    model,
    train_dataset=dataset,
    formatting_func=formatting_prompts_func,
    data_collator=collator,
)

trainer.train()

Popularity 1/10 Helpfulness 1/10 Language python

Source: huggingface.co

Tags: python

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Contributed on Aug 23 2023

Curious Corncrake

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