metadata
base_model:
- google/gemma-2-2b-it
tags:
- merge
- mergekit
- lazymergekit
- google/gemma-2-2b-it
gemma-instruct-merge-ties_0.5
gemma-instruct-merge-ties_0.5 is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: google/gemma-2-2b
- model: google/gemma-2-2b-it
parameters:
density:
- value: 0.5
weight:
- value: 1
merge_method: ties
base_model: google/gemma-2-2b
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
tokenizer_source: union
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "choprahetarth/gemma-instruct-merge-ties_0.5"
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"])