Text Generation
PEFT
Safetensors
English
lori
Mixture of Experts
adapter-routing
hybrid-mamba-attention
emergent-reasoning
lora
science-reasoning
nemotron
mamba
code
science
stem
hybrid-mamba
quantized
4bit
bnb
conversational
Eval Results (legacy)
Instructions to use uditjain/Nemotron-30B-Science-Instruct-LoRI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use uditjain/Nemotron-30B-Science-Instruct-LoRI with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16") model = PeftModel.from_pretrained(base_model, "uditjain/Nemotron-30B-Science-Instruct-LoRI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca6ce91cd63ab3112bd7c2a644a541b6dc59d142c33639d4d6100b15e5129daf
- Size of remote file:
- 17.1 MB
- SHA256:
- cbeec0ecfe1acc44169bf9d17758deab48c4b864cd63c95b050838d0279befaf
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