Instructions to use a2ran/kor_chatGLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use a2ran/kor_chatGLM with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("THUDM/chatglm-6b") model = PeftModel.from_pretrained(base_model, "a2ran/kor_chatGLM") - Notebooks
- Google Colab
- Kaggle
File size: 419 Bytes
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library_name: peft
---
- **WIP**
Data used : https://raw.githubusercontent.com/Beomi/KoAlpaca/main/alpaca_data.json
training_args = TrainingArguments(
"output",
fp16 =True,
gradient_accumulation_steps=1,
per_device_train_batch_size = 1,
learning_rate = 1e-4,
max_steps=3000,
logging_steps=100,
remove_unused_columns=False,
seed=0,
data_seed=0,
group_by_length=False,
) |