Feature Extraction
Transformers
Safetensors
gemma3_text
text-generation
fp8
quantized
embedding
nvidia-modelopt
text-embeddings-inference
Instructions to use 1kxia/gemma-3-270m-modelopt-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1kxia/gemma-3-270m-modelopt-fp8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="1kxia/gemma-3-270m-modelopt-fp8")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("1kxia/gemma-3-270m-modelopt-fp8") model = AutoModelForCausalLM.from_pretrained("1kxia/gemma-3-270m-modelopt-fp8") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!