Text Generation
PEFT
Safetensors
smollm3
lora
context-compression
agent-memory
membrane
conversational
Instructions to use homerquan/mn-context-engine-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use homerquan/mn-context-engine-lora-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolLM3-3B") model = PeftModel.from_pretrained(base_model, "homerquan/mn-context-engine-lora-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91d3a5a67d1dc2437f26de6a19ddc481c50d7a61b91fb2cf77b4152501798598
- Size of remote file:
- 5.27 kB
- SHA256:
- 0f70f4b565a069b8d016b983377b6af78e2ec6b3a4c08291cc485c6ed3940896
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