Spaetzle-v68-7b
Spaetzle-v68-7b is a merge of the following models using
LazyMergekit:
🧩 Configuration
1models:
2 - model: cstr/Spaetzle-v67-7b
3 # no parameters necessary for base model
4 - model: cstr/Spaetzle-v65-7b
5 parameters:
6 density: 0.60
7 weight: 0.30
8 - model: cstr/Spaetzle-v64-7b
9 parameters:
10 density: 0.65
11 weight: 0.30
12merge_method: dare_ties
13base_model: cstr/Spaetzle-v67-7b
14parameters:
15 int8_mask: true
16dtype: bfloat16
17random_seed: 0
18tokenizer_source: base
💻 Usage
1!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "cstr/Spaetzle-v68-7b"
8messages = [{"role": "user", "content": "What is a large language model?"}]
9
10tokenizer = AutoTokenizer.from_pretrained(model)
11prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
12pipeline = transformers.pipeline(
13 "text-generation",
14 model=model,
15 torch_dtype=torch.float16,
16 device_map="auto",
17)
18
19outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
20print(outputs[0]["generated_text"])
EU AI Act Art. 53 — provider obligations
Added 2026-08-02 during an account-wide provenance review.
This is a model merge, not a format conversion. Most cstr/* repositories
are GGUF conversions, where the upstream research team remains the provider of
the model and the conversion changes only the numeric representation of the
weights. A merge produces a model that did not previously exist, so under
Regulation (EU) 2024/1689 the maintainer of this repository is plausibly the
provider of it, and the duties that survive the Art. 53(2)
free-and-open-source exemption — Art. 53(1)(c) and 53(1)(d) — attach here rather
than upstream.
Art. 53(1)(c) — copyright policy. No training corpus was assembled by this
repository. Merging combines weights that other providers already published; it
performs no text or data mining, so no rights reservation under Art. 4(3) of
Directive (EU) 2019/790 was engaged by this step. Copyright questions arising
from how the constituent models were themselves trained attach to their
respective providers. Any credible claim that this repository redistributes
material it has no right to redistribute will be acted on — contact via the
Community tab.
Art. 53(1)(d) — training content. No data was used to train this model: it
is a weight-space combination of models trained by others, and its training
content is theirs. All 2 constituent models this card names are still published, so the chain can be followed from here.
Licence — resolved 2026-08-02. cc-by-nc-sa-4.0. This merge combines two branches carrying different restrictions: cstr/Spaetzle-v64-7b brings CC-BY-SA-4.0 (via ResplendentAI/Flora_DPO_7B) and cstr/Spaetzle-v65-7b brings CC-BY-NC-4.0 (via yleo/EmertonMonarch-7B). Both apply, so the terms here are NonCommercial and ShareAlike.
This was derived from the mergekit configuration reproduced in this card by
resolving each named constituent's licence on the Hub and taking the most
restrictive, rather than assumed from the model family. An earlier revision of
this section said the terms were unresolved; they are resolved now, and the
method is recorded so the conclusion can be checked rather than trusted.