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Model: cstr/llama3.1-8b-spaetzle-v74
Source: Original Platform

.gitattributes

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README.md

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+---
+base_model:
+- cstr/llama3.1-8b-spaetzle-v59
+- cstr/llama3.1-8b-spaetzle-v63
+- cstr/llama3.1-8b-spaetzle-v66
+- cstr/llama3.1-8b-spaetzle-v73
+tags:
+- merge
+- mergekit
+license: llama3.1
+language:
+- en
+- de
+library_name: transformers
+---
+
+# llama3.1-8b-spaetzle-v74
+
+llama3.1-8b-spaetzle-v74 is a merge of the following models:
+* [cstr/llama3.1-8b-spaetzle-v59](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v59)
+* [cstr/llama3.1-8b-spaetzle-v63](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v63)
+* [cstr/llama3.1-8b-spaetzle-v66](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v66)
+* [cstr/llama3.1-8b-spaetzle-v73](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v73)
+
+EQ-Bench v2_de: 68.05 169/171, en: 75.27 - which is not the best, but it produces decent answers for some trick questions, and i have a sweet spot for that ;)
+
+## 🧩 Configuration
+
+```yamlmodels:
+models:
+  - model: cstr/llama3.1-8b-spaetzle-v59
+    parameters:
+      weight: 0.3
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v63
+    parameters:
+      weight: 0.15
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v66
+    parameters:
+      weight: 0.15
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v73
+    parameters:
+      weight: 0.4
+      density: 0.5
+base_model: cstr/llama3.1-8b-spaetzle-v59
+merge_method: della_linear
+parameters:
+  int8_mask: true
+  normalize: true
+  epsilon: 0.1  
+  lambda: 1.0   
+  density: 0.7
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "cstr/llama3.1-8b-spaetzle-v74"
+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"])
+```
+
+## 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. Of the 4 constituent models this card names, **1 are still published and 3 are not**: `cstr/llama3.1-8b-spaetzle-v63`, `cstr/llama3.1-8b-spaetzle-v66`, `cstr/llama3.1-8b-spaetzle-v73`. For those, the training-content chain cannot be followed from this card, and no summary is reconstructed here in their place — an untraceable summary presented as a traceable one would be worse than the gap.

config.json

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+{
+  "_name_or_path": "cstr/llama3.1-8b-spaetzle-v59",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}

mergekit_config.yml

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+models:
+models:
+  - model: cstr/llama3.1-8b-spaetzle-v59
+    parameters:
+      weight: 0.3
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v63
+    parameters:
+      weight: 0.15
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v66
+    parameters:
+      weight: 0.15
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v73
+    parameters:
+      weight: 0.4
+      density: 0.5
+base_model: cstr/llama3.1-8b-spaetzle-v59
+merge_method: della_linear
+parameters:
+  int8_mask: true
+  normalize: true
+  epsilon: 0.1  
+  lambda: 1.0   
+  density: 0.7
+dtype: bfloat16

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special_tokens_map.json

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+{
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+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}