Instructions to use nithinai517/tinyllama-support-dora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nithinai517/tinyllama-support-dora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "nithinai517/tinyllama-support-dora") - Notebooks
- Google Colab
- Kaggle
TinyLlama Customer Support (DoRA)
TinyLlama-1.1B-Chat fine-tuned with DoRA on the Bitext customer support dataset.
- Base model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
- Method: DoRA (r=16, alpha=32, target_modules=q_proj,k_proj,v_proj,o_proj,gate_proj,up_proj,down_proj)
- Data: bitext/Bitext-customer-support-llm-chatbot-training-dataset (5,000 example subsample)
- Final val loss: ~0.638
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch
base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0", torch_dtype=torch.float16, device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("nithinai517/tinyllama-support-dora")
model = PeftModel.from_pretrained(base_model, "nithinai517/tinyllama-support-dora")
- Downloads last month
- 6
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for nithinai517/tinyllama-support-dora
Base model
TinyLlama/TinyLlama-1.1B-Chat-v1.0