Text Generation
PEFT
Safetensors
banking
intent-classification
lora
sft
qlora
unsloth
gemma
fine-tuned
vietnamese
Instructions to use anyu205/banking_intent_gemma2_unsloth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use anyu205/banking_intent_gemma2_unsloth with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-9b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "anyu205/banking_intent_gemma2_unsloth") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use anyu205/banking_intent_gemma2_unsloth with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for anyu205/banking_intent_gemma2_unsloth to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for anyu205/banking_intent_gemma2_unsloth to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for anyu205/banking_intent_gemma2_unsloth to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="anyu205/banking_intent_gemma2_unsloth", max_seq_length=2048, )
| This directory includes a few sample datasets to get you started. | |
| * `california_housing_data*.csv` is California housing data from the 1990 US | |
| Census; more information is available at: | |
| https://docs.google.com/document/d/e/2PACX-1vRhYtsvc5eOR2FWNCwaBiKL6suIOrxJig8LcSBbmCbyYsayia_DvPOOBlXZ4CAlQ5nlDD8kTaIDRwrN/pub | |
| * `mnist_*.csv` is a small sample of the | |
| [MNIST database](https://en.wikipedia.org/wiki/MNIST_database), which is | |
| described at: http://yann.lecun.com/exdb/mnist/ | |
| * `anscombe.json` contains a copy of | |
| [Anscombe's quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet); it | |
| was originally described in | |
| Anscombe, F. J. (1973). 'Graphs in Statistical Analysis'. American | |
| Statistician. 27 (1): 17-21. JSTOR 2682899. | |
| and our copy was prepared by the | |
| [vega_datasets library](https://github.com/altair-viz/vega_datasets/blob/4f67bdaad10f45e3549984e17e1b3088c731503d/vega_datasets/_data/anscombe.json). | |