---

base_model:

• cstr/llama3.1-8b-spaetzle-v85
• cstr/llama3.1-8b-spaetzle-v86
• cstr/llama3.1-8b-spaetzle-v74

tags:

• merge
• mergekit
• lazymergekit
• cstr/llama3.1-8b-spaetzle-v85
• cstr/llama3.1-8b-spaetzle-v86
• cstr/llama3.1-8b-spaetzle-v74

license: llama3

language:

• en
• de

---

llama3.1-8b-spaetzle-v90

These are q4_k_m quants made with llama.cpp b3472 from cstr/llama3.1-8b-spaetzle-v90 which is a progressive merge of merges.

EQ-Bench v2_de: 69.93 (171/171).

The merge tree involves the following models:

• NousResearch/Hermes-3-Llama-3.1-8B
• Undi95/Meta-Llama-3.1-8B-Claude
• Dampfinchen/Llama-3.1-8B-Ultra-Instruct
• VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct
• akjindal53244/Llama-3.1-Storm-8B
• nbeerbower/llama3.1-gutenberg-8B
• Undi95/Meta-Llama-3.1-8B-Claude
• DiscoResearch/Llama3-DiscoLeo-Instruct-8B-v0.1
• nbeerbower/llama-3-wissenschaft-8B-v2
• Azure99/blossom-v5-llama3-8b
• VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
• princeton-nlp/Llama-3-Instruct-8B-SimPO
• Locutusque/llama-3-neural-chat-v1-8b
• Locutusque/Llama-3-Orca-1.0-8B
• DiscoResearch/Llama3_DiscoLM_German_8b_v0.1_experimental
• seedboxai/Llama-3-Kafka-8B-v0.2
• VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
• nbeerbower/llama-3-wissenschaft-8B-v2
• mlabonne/Daredevil-8B-abliterated-dpomix

There have been a number of steps involved, among which, slep merging of only middle layers compensating for tokenizer / chat template differences. An illustration below.

🧩 Configuration

The final merge for this was:

models:
  - model: cstr/llama3.1-8b-spaetzle-v59
    # no parameters necessary for base model
  - model: cstr/llama3.1-8b-spaetzle-v85
    parameters:
      density: 0.65
      weight: 0.3
  - model: cstr/llama3.1-8b-spaetzle-v86
    parameters:
      density: 0.65
      weight: 0.3
  - model: cstr/llama3.1-8b-spaetzle-v74
    parameters:
      density: 0.65
      weight: 0.3
merge_method: dare_ties
base_model: cstr/llama3.1-8b-spaetzle-v59
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0
tokenizer_source: base

Among the previous steps:

models:
  - model: NousResearch/Hermes-3-Llama-3.1-8B
merge_method: slerp
base_model: cstr/llama3.1-8b-spaetzle-v74
parameters:
  t:
    - value: [0, 0, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0, 0]
dtype: float16

💻 Usage

Use with llama3 chat template as common. The q4km quants here are from cstr/llama3.1-8b-spaetzle-v90.

Provenance and EU AI Act Art. 53 note

• Base model: cstr/llama3.1-8b-spaetzle-v90 — 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 (GGUF). 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/llama3.1-8b-spaetzle-v90, not here.