Type	Model	Average ⬆️	ARC-c	ARC-e	Boolq	HellaSwag	Lambada	MMLU	Openbookqa	Piqa	Truthfulqa	Winogrande	#Params (B)	#Size (G)
🍒	cstr/llama3-8b-spaetzle-v20-int4-inc	66.43	61.77	85.4	82.75	62.79	71.73	64.17	37.4	80.41	43.21	74.66	7.04	5.74

🧩 Configuration

yaml

models:
  - model: cstr/llama3-8b-spaetzle-v13
    # no parameters necessary for base model
  - model: nbeerbower/llama-3-wissenschaft-8B-v2
    parameters:
      density: 0.65
      weight: 0.4        
merge_method: dare_ties
base_model: cstr/llama3-8b-spaetzle-v13
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0
tokenizer_source: base

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "cstr/llama3-8b-spaetzle-v20"
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"])

Provenance and EU AI Act Art. 53 note

Base model: cstr/llama3-8b-spaetzle-v20 — a mergekit merge published by the same maintainer as this repository. It is not a third-party upstream: the maintainer authored that model.
What was done here: format conversion and/or quantisation of that base model only (GPTQ, INT4 precision). No further training, fine-tuning or merging was applied at this step.
Licence: llama3, inherited through the base model from the models it was built from.
Training data: none was used, added or selected at this conversion step. The base model's card lists the models it was built from; their training content is documented — where it is documented at all — by their respective providers.
Provider status: under Regulation (EU) 2024/1689 this repository makes no provider claim for the conversion step. Any provider obligations attaching to the model itself — including Art. 53(1)(c) copyright policy and Art. 53(1)(d) training-content summary — attach at cstr/llama3-8b-spaetzle-v20, not here.

cstr/llama3-8b-spaetzle-v20-int4-inc

llama3-8b-spaetzle-v20

Benchmarks

🧩 Configuration

💻 Usage

Provenance and EU AI Act Art. 53 note

cstr/
llama3-8b-spaetzle-v20-int4-inc