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Wiedervereinigung-7b-dpo-laser/README.md ADDED
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+ ---
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+ tags:
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+ - merge
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+ - mergekit
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+ - lazymergekit
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+ - DiscoResearch/DiscoLM_German_7b_v1
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+ - DRXD1000/Phoenix
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+ - VAGOsolutions/SauerkrautLM-7b-v1-mistral
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+ - malteos/hermeo-7b
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+ base_model:
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+ - DiscoResearch/DiscoLM_German_7b_v1
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+ - DRXD1000/Phoenix
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+ - VAGOsolutions/SauerkrautLM-7b-v1-mistral
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+ - malteos/hermeo-7b
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+ ---
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+
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+ # Wiedervereinigung-7b-dpo-laser
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+
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+ ![image/png](https://huggingface.co/mayflowergmbh/Wiedervereinigung-7b/resolve/main/Wiedervereinigung-7b.png)
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+
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+ Some of the best german models with 7b parameters as lasered dpo-trained dare_ties merge.
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+
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+ 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.
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+ 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).
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+ After that this model got a [laserRMT](https://github.com/cognitivecomputations/laserRMT) treatment.
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+
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+ Wiedervereinigung-7b itself is a [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing) merge of:
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+ * [DiscoResearch/DiscoLM_German_7b_v1](https://huggingface.co/DiscoResearch/DiscoLM_German_7b_v1)
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+ * [DRXD1000/Phoenix](https://huggingface.co/DRXD1000/Phoenix)
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+ * [VAGOsolutions/SauerkrautLM-7b-v1-mistral](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-v1-mistral)
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+ * [malteos/hermeo-7b](https://huggingface.co/malteos/hermeo-7b)
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+
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+ All the actual heavylifting has been done by the creators of these models.
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+
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+ ## 🧩 Configuration
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+
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+ ```yaml
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+ models:
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+ - model: LeoLM/leo-mistral-hessianai-7b
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+ # No parameters necessary for base model
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+ - model: DiscoResearch/DiscoLM_German_7b_v1
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+ parameters:
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+ density: 0.6
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+ weight: 0.25
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+ - model: DRXD1000/Phoenix
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+ parameters:
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+ density: 0.6
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+ weight: 0.25
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+ - model: VAGOsolutions/SauerkrautLM-7b-v1-mistral
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+ parameters:
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+ density: 0.6
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+ weight: 0.25
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+ - model: malteos/hermeo-7b
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+ parameters:
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+ density: 0.6
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+ weight: 0.25
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+ merge_method: dare_ties
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+ base_model: LeoLM/leo-mistral-hessianai-7b
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+ parameters:
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+ int8_mask: true
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+ dtype: bfloat16
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+ ```
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+
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+ ## mt-bench-de
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+
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+ Using laser and dpo results in pretty good results.
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+
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+ ```json
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+ {
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+ "first_turn": 7.51875,
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+ "second_turn": 6.4,
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+ "categories": {
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+ "writing": 8.425,
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+ "roleplay": 8.025,
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+ "reasoning": 5.45,
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+ "math": 3.2,
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+ "coding": 4.95,
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+ "extraction": 7.525,
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+ "stem": 8.775,
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+ "humanities": 9.325
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+ },
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+ "average": 6.959375
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+ }
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+
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+ ```
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+
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+ ## 💻 Usage
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+
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+ ```python
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+ !pip install -qU transformers accelerate
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+
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+ from transformers import AutoTokenizer
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+ import transformers
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+ import torch
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+
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+ model = "mayflowergmbh/Wiedervereinigung-7b-dpo-laser"
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+ messages = [{"role": "user", "content": "Was ist ein large language model?"}]
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model)
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+ prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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+ pipeline = transformers.pipeline(
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+ "text-generation",
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+ model=model,
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+ torch_dtype=torch.float16,
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+ device_map="auto",
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+ )
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+
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+ outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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+ print(outputs[0]["generated_text"])
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+ ```
Wiedervereinigung-7b-dpo-laser/added_tokens.json ADDED
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+ {
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+ "</s>": 2,
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+ "<s>": 1,
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+ "<unk>": 0
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+ }
Wiedervereinigung-7b-dpo-laser/config.json ADDED
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+ {
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+ "_name_or_path": "mayflowergmbh/Wiedervereinigung-7b-dpo",
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+ "architectures": [
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+ "MistralForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mistral",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 10000.0,
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+ "sliding_window": 4096,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.34.0",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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