How to use Chilliwiddit/iCliniq-llama3.1-8B-LoRA-pyTorch with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Meta-Llama-3.1-8B-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Chilliwiddit/iCliniq-llama3.1-8B-LoRA-pyTorch")
How to use Chilliwiddit/iCliniq-llama3.1-8B-LoRA-pyTorch with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="Chilliwiddit/iCliniq-llama3.1-8B-LoRA-pyTorch")
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Chilliwiddit/iCliniq-llama3.1-8B-LoRA-pyTorch", device_map="auto")
Basically used to summarize text from the iCliniq dataset.
I used the iCliniq dataset
Training regime: [More Information Needed]
16 Mixed Precision
LR of 0.001
5 Epochs
Base model
