LLM Lora
Collection
16 items • Updated • 3
How to use bunnycore/Qwen-2.5-7B-RRP-v1.1-Lora with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bunnycore/Qwen-2.5-7B-RRP-v1.1-Lora", dtype="auto")How to use bunnycore/Qwen-2.5-7B-RRP-v1.1-Lora with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for bunnycore/Qwen-2.5-7B-RRP-v1.1-Lora to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for bunnycore/Qwen-2.5-7B-RRP-v1.1-Lora to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bunnycore/Qwen-2.5-7B-RRP-v1.1-Lora to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="bunnycore/Qwen-2.5-7B-RRP-v1.1-Lora",
max_seq_length=2048,
)from datasets import load_dataset
dataset = load_dataset("Chaser-cz/sonnet35-charcard-roleplay-sharegpt", split = "train")
from datasets import load_dataset
dataset2 = load_dataset("AMead10/Sky-T1_data_17k_sharegpt", split = "train")
from datasets import load_dataset
dataset3 = load_dataset("Magpie-Align/Magpie-Reasoning-V2-250K-CoT-Deepseek-R1-Llama-70B", split = "train")
This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
Base model
Qwen/Qwen2.5-7B