Text Generation
PEFT
Safetensors
lora
grpo
trl
unsloth
fraud-detection
upi
india
multi-agent
openenv
scalable-oversight
conversational
Eval Results (legacy)
Instructions to use ujjwalpardeshi/chakravyuh-analyzer-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ujjwalpardeshi/chakravyuh-analyzer-lora-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "ujjwalpardeshi/chakravyuh-analyzer-lora-v2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
- Xet hash:
- fc23b0c3ff41a8a1324c8565bce595fe11422393117c438758cc6fcea9be9541
- Size of remote file:
- 11.4 MB
- SHA256:
- bd5948af71b4f56cf697f7580814c7ce8b80595ef985544efcacf716126a2e31
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