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Model: cstr/Spaetzle-v8-7b
Source: Original Platform

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README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- flemmingmiguel/NeuDist-Ro-7B
+- johannhartmann/Brezn3
+- ResplendentAI/Flora_DPO_7B
+base_model:
+- flemmingmiguel/NeuDist-Ro-7B
+- johannhartmann/Brezn3
+- ResplendentAI/Flora_DPO_7B
+language:
+- de
+- en
+---
+
+# Spaetzle-v8-7b
+
+This model is supposed to show adequate performance in German and English on a number of tasks, while mostly behaving well, that is, without rambling on, intermixing tokens from different templates in training and adapting, etc.
+
+It is mostly a quick test, and considerably weaker in German grammar and orthography than DiscoLM e.g., but for use cases where this is not too important, but e.g. instruction following, reasoning, etc, it might actually be a little bit preferable.
+
+It is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [flemmingmiguel/NeuDist-Ro-7B](https://huggingface.co/flemmingmiguel/NeuDist-Ro-7B)
+* [johannhartmann/Brezn3](https://huggingface.co/johannhartmann/Brezn3)
+* [ResplendentAI/Flora_DPO_7B](https://huggingface.co/ResplendentAI/Flora_DPO_7B)
+* on the basis of [mayflowergmbh/Wiedervereinigung-7b-dpo-laser](https://huggingface.co/mayflowergmbh/Wiedervereinigung-7b-dpo-laser)
+
+All credits are due to the creators of those original models and the training datasets involved.
+
+For a suitable quantized version, try [cstr/Spaetzle-v8-7b-GGUF](https://huggingface.co/cstr/Spaetzle-v8-7b-GGUF)
+
+
+## Evaluation
+[Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_cstr__Spaetzle-v8-7b)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |72.27|
+|AI2 Reasoning Challenge (25-Shot)|68.69|
+|HellaSwag (10-Shot)              |86.68|
+|MMLU (5-Shot)                    |64.60|
+|TruthfulQA (0-shot)              |64.05|
+|Winogrande (5-shot)              |81.45|
+|GSM8k (5-shot)                   |68.16|
+
+EQ-Bench (v2_de): 61.04 / english (v2): 78.3
+
+[ScandEval](https://scandeval.com/german-nlg/) 12.5.2 scores 
+
+| Benchmark             | Spaetzle-v8-7b Value                               |
+|-----------------------|----------------------------------------------------|
+| Model ID              | cstr/Spaetzle-v8-7b (few-shot, val)                |
+| Parameters            | 7242                                               |
+| Vocabulary Size       | 32                                                 |
+| Context               | 32768                                              |
+| Commercial            | False                                              |
+| Speed                 | 5,980 ± 1,031 / 1,714 ± 552                        |
+| Rank                  | 1.85                                               |
+| GermEval              | 58.90 ± 2.30 / 45.55 ± 3.30                        |
+| SB10k                 | 61.34 ± 1.90 / 72.98 ± 1.30                        |
+| ScaLA-De              | 31.58 ± 4.39 / 65.51 ± 2.23                        |
+| GermanQuAD            | 24.91 ± 3.98 / 60.88 ± 3.31                        |
+| MLSum                 | 67.25 ± 1.06 / 22.95 ± 2.64                        |
+| MMLU-De               | 34.62 ± 2.20 / 50.43 ± 1.52                        |
+| HellaSwag-De          | 48.70 ± 2.47 / 61.05 ± 1.79                        |
+
+
+|                           Model                            |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
+|------------------------------------------------------------|------:|------:|---------:|-------:|------:|
+|[Spaetzle-v8-7b](https://huggingface.co/cstr/Spaetzle-v8-7b)|  45.31|  75.69|     63.94|   45.57|  57.63|
+
+### AGIEval
+|             Task             |Version| Metric |Value|   |Stderr|
+|------------------------------|------:|--------|----:|---|-----:|
+|agieval_aqua_rat              |      0|acc     |25.59|±  |  2.74|
+|                              |       |acc_norm|24.80|±  |  2.72|
+|agieval_logiqa_en             |      0|acc     |39.63|±  |  1.92|
+|                              |       |acc_norm|39.78|±  |  1.92|
+|agieval_lsat_ar               |      0|acc     |23.48|±  |  2.80|
+|                              |       |acc_norm|24.35|±  |  2.84|
+|agieval_lsat_lr               |      0|acc     |50.98|±  |  2.22|
+|                              |       |acc_norm|51.96|±  |  2.21|
+|agieval_lsat_rc               |      0|acc     |62.08|±  |  2.96|
+|                              |       |acc_norm|62.83|±  |  2.95|
+|agieval_sat_en                |      0|acc     |78.64|±  |  2.86|
+|                              |       |acc_norm|79.13|±  |  2.84|
+|agieval_sat_en_without_passage|      0|acc     |44.66|±  |  3.47|
+|                              |       |acc_norm|44.66|±  |  3.47|
+|agieval_sat_math              |      0|acc     |37.27|±  |  3.27|
+|                              |       |acc_norm|35.00|±  |  3.22|
+
+Average: 45.31%
+
+### GPT4All
+|    Task     |Version| Metric |Value|   |Stderr|
+|-------------|------:|--------|----:|---|-----:|
+|arc_challenge|      0|acc     |63.14|±  |  1.41|
+|             |       |acc_norm|64.51|±  |  1.40|
+|arc_easy     |      0|acc     |85.98|±  |  0.71|
+|             |       |acc_norm|82.49|±  |  0.78|
+|boolq        |      1|acc     |88.10|±  |  0.57|
+|hellaswag    |      0|acc     |66.31|±  |  0.47|
+|             |       |acc_norm|85.17|±  |  0.35|
+|openbookqa   |      0|acc     |38.00|±  |  2.17|
+|             |       |acc_norm|47.20|±  |  2.23|
+|piqa         |      0|acc     |83.35|±  |  0.87|
+|             |       |acc_norm|84.17|±  |  0.85|
+|winogrande   |      0|acc     |78.22|±  |  1.16|
+
+Average: 75.69%
+
+### TruthfulQA
+|    Task     |Version|Metric|Value|   |Stderr|
+|-------------|------:|------|----:|---|-----:|
+|truthfulqa_mc|      1|mc1   |47.74|±  |  1.75|
+|             |       |mc2   |63.94|±  |  1.53|
+
+Average: 63.94%
+
+### Bigbench
+|                      Task                      |Version|       Metric        |Value|   |Stderr|
+|------------------------------------------------|------:|---------------------|----:|---|-----:|
+|bigbench_causal_judgement                       |      0|multiple_choice_grade|56.84|±  |  3.60|
+|bigbench_date_understanding                     |      0|multiple_choice_grade|66.12|±  |  2.47|
+|bigbench_disambiguation_qa                      |      0|multiple_choice_grade|41.47|±  |  3.07|
+|bigbench_geometric_shapes                       |      0|multiple_choice_grade|22.01|±  |  2.19|
+|                                                |       |exact_str_match      | 0.00|±  |  0.00|
+|bigbench_logical_deduction_five_objects         |      0|multiple_choice_grade|31.40|±  |  2.08|
+|bigbench_logical_deduction_seven_objects        |      0|multiple_choice_grade|23.14|±  |  1.60|
+|bigbench_logical_deduction_three_objects        |      0|multiple_choice_grade|56.00|±  |  2.87|
+|bigbench_movie_recommendation                   |      0|multiple_choice_grade|45.00|±  |  2.23|
+|bigbench_navigate                               |      0|multiple_choice_grade|50.70|±  |  1.58|
+|bigbench_reasoning_about_colored_objects        |      0|multiple_choice_grade|70.05|±  |  1.02|
+|bigbench_ruin_names                             |      0|multiple_choice_grade|45.54|±  |  2.36|
+|bigbench_salient_translation_error_detection    |      0|multiple_choice_grade|26.05|±  |  1.39|
+|bigbench_snarks                                 |      0|multiple_choice_grade|71.82|±  |  3.35|
+|bigbench_sports_understanding                   |      0|multiple_choice_grade|72.92|±  |  1.42|
+|bigbench_temporal_sequences                     |      0|multiple_choice_grade|44.20|±  |  1.57|
+|bigbench_tracking_shuffled_objects_five_objects |      0|multiple_choice_grade|22.80|±  |  1.19|
+|bigbench_tracking_shuffled_objects_seven_objects|      0|multiple_choice_grade|18.23|±  |  0.92|
+|bigbench_tracking_shuffled_objects_three_objects|      0|multiple_choice_grade|56.00|±  |  2.87|
+
+Average: 45.57%
+
+Average score: 57.63%
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "cstr/Spaetzle-v8-7b"
+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"])
+```
+
+
+## 🧩 Configuration
+
+The model uses ChatML and should work well with this (as it is merged from models which (mostly) saw ChatML templates in training). 
+
+```yaml
+models:
+  - model: mayflowergmbh/Wiedervereinigung-7b-dpo-laser
+    # no parameters necessary for base model
+  - model: flemmingmiguel/NeuDist-Ro-7B
+    parameters:
+      density: 0.60
+      weight: 0.30
+  - model: johannhartmann/Brezn3
+    parameters:
+      density: 0.65
+      weight: 0.40
+  - model: ResplendentAI/Flora_DPO_7B
+    parameters:
+      density: 0.6
+      weight: 0.3
+merge_method: dare_ties
+base_model: mayflowergmbh/Wiedervereinigung-7b-dpo-laser
+parameters:
+  int8_mask: true
+dtype: bfloat16
+random_seed: 0
+tokenizer_source: base
+```

config.json

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+{
+  "_name_or_path": "mayflowergmbh/Wiedervereinigung-7b-dpo-laser",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+
+models:
+  - model: mayflowergmbh/Wiedervereinigung-7b-dpo-laser
+    # no parameters necessary for base model
+  - model: flemmingmiguel/NeuDist-Ro-7B
+    parameters:
+      density: 0.60
+      weight: 0.30
+  - model: johannhartmann/Brezn3
+    parameters:
+      density: 0.65
+      weight: 0.40
+  - model: ResplendentAI/Flora_DPO_7B
+    parameters:
+      density: 0.6
+      weight: 0.3
+merge_method: dare_ties
+base_model: mayflowergmbh/Wiedervereinigung-7b-dpo-laser
+parameters:
+  int8_mask: true
+dtype: bfloat16
+random_seed: 0
+tokenizer_source: base

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special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<unk>",
+    "<s>",
+    "</s>"
+  ],
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<unk>",
+    "<s>",
+    "</s>"
+  ],
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content']}}{% if (loop.last and add_generation_prompt) or not loop.last %}{{ '<|im_end|>' + '\n'}}{% endif %}{% endfor %}\n{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "split_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}