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VSFT hotfix - adds gen prompt to template and processor to hub #1532

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merged 2 commits into from
Apr 12, 2024
Merged

VSFT hotfix - adds gen prompt to template and processor to hub #1532

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77d2dc8
adds gen prompt to template and processor to hub
edbeeching Apr 12, 2024
6010b30
fixes hub model id, removes Path
edbeeching Apr 12, 2024
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5 changes: 4 additions & 1 deletion examples/scripts/vsft_llava.py
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Original file line number Diff line number Diff line change
Expand Up @@ -79,6 +79,7 @@
from rich.logging import RichHandler

import torch
from accelerate import Accelerator
from datasets import load_dataset

from tqdm.rich import tqdm
Expand Down Expand Up @@ -111,7 +112,7 @@
################
# Model, Tokenizer & Processor
################
LLAVA_CHAT_TEMPLATE = """A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. {% for message in messages %}{% if message['role'] == 'user' %}USER: {% else %}ASSISTANT: {% endif %}{% for item in message['content'] %}{% if item['type'] == 'text' %}{{ item['text'] }}{% elif item['type'] == 'image' %}<image>{% endif %}{% endfor %}{% if message['role'] == 'user' %} {% else %}{{eos_token}}{% endif %}{% endfor %}"""
LLAVA_CHAT_TEMPLATE = """{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. {% for message in messages %}{% if message['role'] == 'user' %}USER: {% else %}ASSISTANT: {% endif %}{% for item in message['content'] %}{% if item['type'] == 'text' %}{{ item['text'] }}{% elif item['type'] == 'image' %}<image>{% endif %}{% endfor %}{% if message['role'] == 'user' %} {% else %}{{eos_token}}{% endif %}{% endfor %}{% if add_generation_prompt %}ASSISTANT: {% endif %}"""

torch_dtype = (
model_config.torch_dtype
Expand Down Expand Up @@ -205,3 +206,5 @@ def __call__(self, examples):
with save_context:
trainer.save_model(training_args.output_dir)
trainer.push_to_hub()
if Accelerator().is_main_process:
processor.push_to_hub(training_args.hub_model_id)
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