README.md

metadata

base_model:
  - google/gemma-2-2b-it
  - Kukedlc/Gemma-2-2B-Spanish-1.0
tags:
  - merge
  - mergekit
  - lazymergekit
  - google/gemma-2-2b-it
  - Kukedlc/Gemma-2-2B-Spanish-1.0
  - autoquant
  - gguf

Kukedlc/NeuralGemma2-2b-Spanish

NeuralGemma-2B-Slerp is a merge of the following models using LazyMergekit:

• google/gemma-2-2b-it
• Kukedlc/Gemma-2-2B-Spanish-1.0

🧩 Configuration

models:
  - model: google/gemma-2-2b
    # No parameters necessary for base model
  - model: google/gemma-2-2b-it
    parameters:
      density: 0.55
      weight: 0.6
  - model: Kukedlc/Gemma-2-2B-Spanish-1.0
    parameters:
      density: 0.55
      weight: 0.4
merge_method: dare_ties
base_model: google/gemma-2-2b
parameters:
  int8_mask: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/NeuralGemma-2B-Slerp"
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"])