Text Generation
PEFT
Safetensors
English
coreference-resolution
ner
entity-extraction
qwen3
lora
conversational
Instructions to use wjbmattingly/Qwen3-8B-Coref-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use wjbmattingly/Qwen3-8B-Coref-NER with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "wjbmattingly/Qwen3-8B-Coref-NER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a6d7494002e95432d8b95dc49f4aa0b0c433af69d49b29322032ce43fb9b632
- Size of remote file:
- 5.33 GB
- SHA256:
- 34357c2e564432b2cb4a560dd6b43843e1b736e4dc134193a1e1cebb5f215f96
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