Text Generation
PEFT
Safetensors
English
argument-mining
fact-checking
information-extraction
lora
qwen2
research
conversational
Instructions to use iamjayeshc/ArgParser-v2-Qwen1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use iamjayeshc/ArgParser-v2-Qwen1.5B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct") model = PeftModel.from_pretrained(base_model, "iamjayeshc/ArgParser-v2-Qwen1.5B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd7b2e2555f97c60783ae78658ea3739a36150a9baa8e74a13d5175b83f6b155
- Size of remote file:
- 988 Bytes
- SHA256:
- 1c727a1fa2ac82030a89dbe95e299a001ac7f361424036928750e97c017c4da6
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