Text Generation
PEFT
Safetensors
English
relation-extraction
information-extraction
literary-nlp
qlora
lora
llama
nlp
conversational
Instructions to use Despina/Llama-3.2-3B-Instruct-re_mixtune-2-shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Despina/Llama-3.2-3B-Instruct-re_mixtune-2-shot with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "Despina/Llama-3.2-3B-Instruct-re_mixtune-2-shot") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bc01b8184a0015b9d9aee62d2fe4a9c912bd2583dbdd5407ac79aac50e970e4
- Size of remote file:
- 389 MB
- SHA256:
- 6988ec21bc53592a264d895ddb038031fbac489bdc9762e932a2f24d9154ebae
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