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
File size: 264 Bytes
05532c9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
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"do_sample": true,
"eos_token_id": [
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151643
],
"max_length": 32768,
"pad_token_id": 151665,
"repetition_penalty": 1.1,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8,
"transformers_version": "5.5.0"
}
|