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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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+ - mlabonne/AlphaMonarch-7B
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+ - Kukedlc/NeuralMaxime-7B-slerp
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+ - bardsai/jaskier-7b-dpo-v5.6
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+ base_model:
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+ - mlabonne/AlphaMonarch-7B
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+ - Kukedlc/NeuralMaxime-7B-slerp
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+ - bardsai/jaskier-7b-dpo-v5.6
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+ ---
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+
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+ # MonaTrix-v6
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+
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+ MonaTrix-v6 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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+ * [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
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+ * [Kukedlc/NeuralMaxime-7B-slerp](https://huggingface.co/Kukedlc/NeuralMaxime-7B-slerp)
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+ * [bardsai/jaskier-7b-dpo-v5.6](https://huggingface.co/bardsai/jaskier-7b-dpo-v5.6)
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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: eren23/dpo-binarized-NeutrixOmnibe-7B
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+ # No parameters necessary for base model
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+ - model: mlabonne/AlphaMonarch-7B
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+ #Emphasize the beginning of Vicuna format models
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+ parameters:
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+ weight: 0.6
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+ density: 0.59
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+ - model: Kukedlc/NeuralMaxime-7B-slerp
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+ parameters:
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+ weight: 0.1
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+ density: 0.55
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+ # Vicuna format
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+ - model: bardsai/jaskier-7b-dpo-v5.6
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+ parameters:
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+ weight: 0.3
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+ density: 0.55
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+
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+ merge_method: dare_ties
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+ base_model: eren23/dpo-binarized-NeutrixOmnibe-7B
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+ parameters:
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+ int8_mask: true
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+ dtype: bfloat16
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+ random_seed: 0
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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 = "CultriX/MonaTrix-v6"
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+ messages = [{"role": "user", "content": "What is a 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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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "eren23/dpo-binarized-NeutrixOmnibe-7B",
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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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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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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": "4.35.2",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
mergekit_config.yml ADDED
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+
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+ models:
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+ - model: eren23/dpo-binarized-NeutrixOmnibe-7B
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+ # No parameters necessary for base model
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+ - model: mlabonne/AlphaMonarch-7B
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+ #Emphasize the beginning of Vicuna format models
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+ parameters:
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+ weight: 0.6
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+ density: 0.59
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+ - model: Kukedlc/NeuralMaxime-7B-slerp
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+ parameters:
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+ weight: 0.1
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+ density: 0.55
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+ # Vicuna format
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+ - model: bardsai/jaskier-7b-dpo-v5.6
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+ parameters:
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+ weight: 0.3
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+ density: 0.55
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+
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+ merge_method: dare_ties
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+ base_model: eren23/dpo-binarized-NeutrixOmnibe-7B
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+ parameters:
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+ int8_mask: true
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+ dtype: bfloat16
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+ random_seed: 0
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