Reinforcement Learning
PEFT
Safetensors
qwen2
openenv
logistics
grpo
unsloth
trl
4-bit precision
bitsandbytes
Instructions to use Leavin1611/logistics-hackathon-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Leavin1611/logistics-hackathon-model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Leavin1611/logistics-hackathon-model") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from Leavin1611/logistics-hackathon-model: direct link, hf CLI and curl.
- Browser
- Download file 73.9 MB
-
https://huggingface.co/Leavin1611/logistics-hackathon-model/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://Leavin1611/logistics-hackathon-model/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/Leavin1611/logistics-hackathon-model/resolve/main/adapter_model.safetensors
73.9 MB
- Xet hash:
- d7e7cffc8f605813c956ad427b0c712d256c2a3638925f678bbb2e40fafdab9c
- Size of remote file:
- 73.9 MB
- SHA256:
- 68fbff27eff594b4f1d184851dc5d988641eec903253d3323540841848dc9976
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