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README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- DiscoResearch/DiscoLM_German_7b_v1
+- DRXD1000/Phoenix
+- VAGOsolutions/SauerkrautLM-7b-v1-mistral
+- malteos/hermeo-7b
+base_model:
+- DiscoResearch/DiscoLM_German_7b_v1
+- DRXD1000/Phoenix
+- VAGOsolutions/SauerkrautLM-7b-v1-mistral
+- malteos/hermeo-7b
+---
+
+# Wiedervereinigung-7b-dpo-laser
+
+![image/png](https://huggingface.co/mayflowergmbh/Wiedervereinigung-7b/resolve/main/Wiedervereinigung-7b.png)
+
+Some of the best german models with 7b parameters as lasered dpo-trained dare_ties merge. 
+
+Since the original models based on mistral - three of them on the brilliant german LeoLM/leo-mistral-hessianai-7b - they are reunited in this merged model. 
+Hence the name. To improve result quality they are dpo-trained with a german translation of oaast-dpo using our german fork of [LLaMA-Factory](https://github.com/mayflower/LLaMA-Factory).
+After that this model got a [laserRMT](https://github.com/cognitivecomputations/laserRMT) treatment.
+
+Wiedervereinigung-7b itself is a  [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing) merge of:
+* [DiscoResearch/DiscoLM_German_7b_v1](https://huggingface.co/DiscoResearch/DiscoLM_German_7b_v1)
+* [DRXD1000/Phoenix](https://huggingface.co/DRXD1000/Phoenix)
+* [VAGOsolutions/SauerkrautLM-7b-v1-mistral](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-v1-mistral)
+* [malteos/hermeo-7b](https://huggingface.co/malteos/hermeo-7b)
+
+All the actual heavylifting has been done by the creators of these models.
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: LeoLM/leo-mistral-hessianai-7b
+    # No parameters necessary for base model
+  - model: DiscoResearch/DiscoLM_German_7b_v1
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: DRXD1000/Phoenix
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: VAGOsolutions/SauerkrautLM-7b-v1-mistral
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: malteos/hermeo-7b
+    parameters:
+      density: 0.6
+      weight: 0.25
+merge_method: dare_ties
+base_model: LeoLM/leo-mistral-hessianai-7b
+parameters:
+  int8_mask: true
+dtype: bfloat16
+```
+
+## mt-bench-de
+
+Using laser and dpo results in pretty good results.
+
+```json
+{
+    "first_turn": 7.51875,
+    "second_turn": 6.4,
+    "categories": {
+        "writing": 8.425,
+        "roleplay": 8.025,
+        "reasoning": 5.45,
+        "math": 3.2,
+        "coding": 4.95,
+        "extraction": 7.525,
+        "stem": 8.775,
+        "humanities": 9.325
+    },
+    "average": 6.959375
+}
+
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "mayflowergmbh/Wiedervereinigung-7b-dpo-laser"
+messages = [{"role": "user", "content": "Was ist ein 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"])
+```

added_tokens.json

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+{
+  "</s>": 2,
+  "<s>": 1,
+  "<unk>": 0
+}

config.json

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+{
+  "_name_or_path": "mayflowergmbh/Wiedervereinigung-7b-dpo",
+  "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": "4.34.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.34.0"
+}

job_new.json

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+{
+    "in_dir": "base_model",
+    "out_dir": "quant",
+    "cal_dataset": "wiki_de_exzellent.parquet",
+    "bits": 5.0,
+    "dataset_rows": 100,
+    "measurement_rows": 16,
+    "length": 2048,
+    "measurement_length": 2048,
+    "head_bits": 6,
+    "shard_size": 8192,
+    "compile_full": null,
+    "rope_scale": null,
+    "rope_alpha": null,
+    "output_measurement": null,
+    "progress": "begin"
+}

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+      "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>",
+  "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
+}