cstr/Spaetzle-v60-7b-Q4_0-GGUF overview
Spaetzle v60 7b This is progressive mostly dare ties, but also slerp merge with the intention of suitable compromise for English and German local tasks. Spaetz…
Runs locally from ~3.83 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Spaetzle-v60-7b_Q4_0.gguf | GGUF | Q4_0 | 3.83 GB | Download |
Model Details
Model README
---
tags:
- merge
- mergekit
- lazymergekit
- abideen/AlphaMonarch-dora
base_model:
- abideen/AlphaMonarch-dora
license: cc-by-nc-4.0
language:
- de
- en
---
Spaetzle-v60-7b
This is progressive (mostly dare-ties, but also slerp) merge with the intention of suitable compromise for English and German local tasks.
Spaetzle-v60-7b is a merge of the following models
Benchmarks
The performance looks ok so far: e.g. we get (for the GGUF q4) in EQ-Bench: Score (v2_de): 65.08 (Parseable: 171.0).
From Low-bit Quantized Open LLM Leaderboard
| Type | Model | Average ⬆️ | ARC-c | ARC-e | Boolq | HellaSwag | Lambada | MMLU | Openbookqa | Piqa | Truthfulqa | Winogrande | #Params (B) | #Size (G) |
|------|-------------------------------------------|------------|-------|-------|-------|-----------|---------|-------|------------|-------|------------|------------|-------------|-----------|
| 🍒 | Intel/SOLAR-10.7B-Instruct-v1.0-int4-inc | 68.49 | 60.49 | 82.66 | 88.29 | 68.29 | 73.36 | 62.43 | 35.6 | 80.74 | 56.06 | 76.95 | 10.57 | 5.98 |
| 🍒 | cstr/Spaetzle-v60-7b-int4-inc | 68.01 | 62.12 | 85.27 | 87.34 | 66.43 | 70.58 | 61.39 | 37 | 82.26 | 50.18 | 77.51 | 7.04 | 4.16 |
| 🔷 | TheBloke/SOLAR-10.7B-Instruct-v1.0-GGUF | 66.6 | 60.41 | 83.38 | 88.29 | 67.73 | 52.42 | 62.04 | 37.2 | 82.32 | 56.3 | 75.93 | 10.73 | 6.07 |
| 🔷 | cstr/Spaetzle-v60-7b-Q4_0-GGUF | 66.44 | 61.35 | 85.19 | 87.98 | 66.54 | 52.78 | 62.05 | 40.6 | 81.72 | 47 | 79.16 | 7.24 | 4.11 |
| 🍒 | Intel/Mistral-7B-Instruct-v0.2-int4-inc | 65.73 | 55.38 | 81.44 | 85.26 | 65.67 | 70.89 | 58.66 | 34.2 | 80.74 | 51.16 | 73.95 | 7.04 | 4.16 |
| 🍒 | Intel/Phi-3-mini-4k-instruct-int4-inc | 65.09 | 57.08 | 83.33 | 86.18 | 59.45 | 68.14 | 66.62 | 38.6 | 79.33 | 38.68 | 73.48 | 3.66 | 2.28 |
| 🔷 | TheBloke/Mistral-7B-Instruct-v0.2-GGUF | 63.52 | 53.5 | 77.9 | 85.44 | 66.9 | 50.11 | 58.45 | 38.8 | 77.58 | 53.12 | 73.4 | 7.24 | 4.11 |
| 🍒 | Intel/Meta-Llama-3-8B-Instruct-int4-inc | 62.93 | 51.88 | 81.1 | 83.21 | 57.09 | 71.32 | 62.41 | 35.2 | 78.62 | 36.35 | 72.14 | 7.2 | 5.4 |
Provenance and EU AI Act Art. 53 note
- Base model: cstr/Spaetzle-v60-7b — 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, INT4 precision). No further training, fine-tuning or merging was applied at this step.
- Licence:
cc-by-nc-4.0, 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/Spaetzle-v60-7b, not here.
Run cstr/Spaetzle-v60-7b-Q4_0-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models