Text Generation
PEFT
Safetensors
English
llama
lora
political-science
survey-replication
canadian-election-study
unsloth
conversational
Instructions to use baglecake/ces-phase3a-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use baglecake/ces-phase3a-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/meta-llama-3.1-8b-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "baglecake/ces-phase3a-lora") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download checkpoint-2000/optimizer.pt from baglecake/ces-phase3a-lora: direct link, hf CLI and curl.
- Browser
- Download file 171 MB
-
https://huggingface.co/baglecake/ces-phase3a-lora/resolve/main/checkpoint-2000/optimizer.pt
- Command line
-
hf download hf://baglecake/ces-phase3a-lora/checkpoint-2000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/baglecake/ces-phase3a-lora/resolve/main/checkpoint-2000/optimizer.pt
171 MB
- Xet hash:
- ed7d47f20fb42f606ce8ccbda02d435a8dc72ca05d13e15312ef471dcefd8f3b
- Size of remote file:
- 171 MB
- SHA256:
- d678a46d5af71c63ddf53122acef82e55bd992dbad0fd11bcf928a8438ed4297
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