Text Generation
PEFT
Safetensors
English
relation-extraction
information-extraction
qlora
lora
nlp
conversational
Instructions to use Despina/Qwen2.5-0.5B-Instruct-re_gentune-2-shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Despina/Qwen2.5-0.5B-Instruct-re_gentune-2-shot with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "Despina/Qwen2.5-0.5B-Instruct-re_gentune-2-shot") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 020f37cc342a7b960aa5aaa1ec6d657d7cc06bf975f8bc7c2e59c85fcaa6e9cc
- Size of remote file:
- 70.4 MB
- SHA256:
- 5afab7118cde4cf5fd2b6d64ac728922803739964074f4fc6b47578e77508fbb
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