metadata
base_model:
- unsloth/gemma-3-4b-it
- vanta-research/scout-4b
tags:
- merge
- mergekit
- lazymergekit
- unsloth/gemma-3-4b-it
- vanta-research/scout-4b
gemma-3-4B_Test1
gemma-3-4B_Test1 is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: unsloth/gemma-3-4b-it
#no parameters necessary for base model
- model: unsloth/gemma-3-4b-it
parameters:
density: 0.477
weight: 0.522
- model: vanta-research/scout-4b
parameters:
density: 0.522
weight: 0.477
merge_method: dare_ties
base_model: unsloth/gemma-3-4b-it
parameters:
normalize: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "zelk12/gemma-3-4B_Test1"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])