README.md

metadata

base_model:
  - Dampfinchen/Llama-3.1-8B-Ultra-Instruct
tags:
  - merge
  - mergekit
  - Undi95/Meta-Llama-3.1-8B-Claude
  - Dampfinchen/Llama-3.1-8B-Ultra-Instruct
license: llama3.1
language:
  - en
  - de

llama3.1-8b-spaetzle-v59

llama3.1-8b-spaetzle-v59 is a dare ties merge of the models

• Undi95/Meta-Llama-3.1-8B-Claude
• Dampfinchen/Llama-3.1-8B-Ultra-Instruct

EQ-Bench v2_de: 67.38 (171/171) (which is not bad...) with q4 quants: cstr/llama3.1-8b-spaetzle-v59-GGUF

🧩 Configuration

models:
  - model: Dampfinchen/Llama-3.1-8B-Ultra-Instruct
    # no parameters necessary for base model
  - model: Undi95/Meta-Llama-3.1-8B-Claude
    parameters:
      density: 0.65
      weight: 0.4
merge_method: dare_ties
base_model: Dampfinchen/Llama-3.1-8B-Ultra-Instruct
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0
tokenizer_source: base

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "cstr/llama3.1-8b-spaetzle-v59"
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"])