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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - merge
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+ - mergekit
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+ - lazymergekit
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+ - nfaheem/Marcoroni-7b-DPO-Merge
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+ - EmbeddedLLM/Mistral-7B-Merge-14-v0.5
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+ ---
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+
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+ # MarcMistral-7B
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+
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+ MarcMistral-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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+ * [nfaheem/Marcoroni-7b-DPO-Merge](https://huggingface.co/nfaheem/Marcoroni-7b-DPO-Merge)
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+ * [EmbeddedLLM/Mistral-7B-Merge-14-v0.5](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.5)
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+
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+ As an experiment to find the best base merge to further fine-tuning, expect a lot of experiments named using parts of the component models until a clear winner emerges in the benchmarks
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+
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+ In this case .
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+
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+ ## 🧩 Configuration
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+
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+ ```yaml
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+ slices:
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+ - sources:
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+ - model: nfaheem/Marcoroni-7b-DPO-Merge
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+ layer_range: [0, 32]
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+ - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.5
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+ layer_range: [0, 32]
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+
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+ merge_method: slerp
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+ base_model: EmbeddedLLM/Mistral-7B-Merge-14-v0.5
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+
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+ parameters:
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+ t:
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5 # fallback for rest of tensors
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+ tokenizer_source: union
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+
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+ dtype: bfloat16
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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 = "flemmingmiguel/MarcMistral-7B"
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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": "EmbeddedLLM/Mistral-7B-Merge-14-v0.5",
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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": 32002
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+ }
mergekit_config.yml ADDED
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+
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+ slices:
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+ - sources:
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+ - model: nfaheem/Marcoroni-7b-DPO-Merge
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+ layer_range: [0, 32]
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+ - model: EmbeddedLLM/Mistral-7B-Merge-14-v0.5
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+ layer_range: [0, 32]
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+
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+ merge_method: slerp
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+ base_model: EmbeddedLLM/Mistral-7B-Merge-14-v0.5
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+
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+ parameters:
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+ t:
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5 # fallback for rest of tensors
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+ tokenizer_source: union
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+
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+ dtype: bfloat16
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