Text Generation
PEFT
Safetensors
English
trading
finance
hyperliquid
perpetuals
defi
lora
dpo
sft
trl
conversational
Instructions to use UVLabs/HyperLLM-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use UVLabs/HyperLLM-4b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507") model = PeftModel.from_pretrained(base_model, "UVLabs/HyperLLM-4b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 654efe6d141e1cf4b560f3a44e7df5277616bdb871783a20b195f35b8e2bee3d
- Size of remote file:
- 5.43 kB
- SHA256:
- 515b2582e2966ea60f1ed5c91af0d9d98e26a7db11d0e149f5a38da2ff983e38
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