Instructions to use mistral-hackaton-2026/ecotopia-citizens-24b-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mistral-hackaton-2026/ecotopia-citizens-24b-merged with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-Small-Instruct-2409") model = PeftModel.from_pretrained(base_model, "mistral-hackaton-2026/ecotopia-citizens-24b-merged") - Notebooks
- Google Colab
- Kaggle
Ecotopia Citizens 24B (LoRA Adapter)
This model is a LoRA fine-tune of mistralai/Mistral-Small-Instruct-2409.
Note: This repo contains the unmerged LoRA adapter. To use:
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-Small-Instruct-2409", torch_dtype="float16", device_map="auto")
model = PeftModel.from_pretrained(base, "mistral-hackaton-2026/ecotopia-citizens-24b-merged")
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-Small-Instruct-2409")
For merged weights, load and call model.merge_and_unload() on a machine with ≥48GB RAM.
Adapter source: mistral-hackaton-2026/ecotopia-citizens-small-22b
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