Question Answering
PEFT
Safetensors
Transformers
English
gemma
lora
sft
4bit
trl
merged
qa
instruction-tuned
270m
Instructions to use sweatSmile/Gemma-3-270m-Buddha-QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sweatSmile/Gemma-3-270m-Buddha-QA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-270m") model = PeftModel.from_pretrained(base_model, "sweatSmile/Gemma-3-270m-Buddha-QA") - Transformers
How to use sweatSmile/Gemma-3-270m-Buddha-QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="sweatSmile/Gemma-3-270m-Buddha-QA")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sweatSmile/Gemma-3-270m-Buddha-QA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "boi_token": "<start_of_image>", | |
| "bos_token": { | |
| "content": "<bos>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eoi_token": "<end_of_image>", | |
| "eos_token": { | |
| "content": "<eos>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "image_token": "<image_soft_token>", | |
| "pad_token": "<eos>", | |
| "unk_token": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |