--- license: apache-2.0 tags: - merge - mergekit - mistral - 7b - lazymergekit - mistralai/Mistral-7B-Instruct-v0.2 - mlabonne/NeuralHermes-2.5-Mistral-7B --- # NeuralHermes-2.5-Mistral-7B-Mistral-7B-Instruct-v0.2-slerp NeuralHermes-2.5-Mistral-7B-Mistral-7B-Instruct-v0.2-slerp is a merge of the following models: * [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) * [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B) ## Eval ``` | Groups |Version|Filter|n-shot| Metric | Value | |Stderr| |------------------|-------|------|-----:|-----------|------:|---|-----:| |ai2_arc |N/A |none | 0|acc | 0.7508|± |0.0419| | | |none | 0|acc_norm | 0.7393|± |0.0354| |mmlu |N/A |none | 0|acc | 0.6082|± |0.1381| | - humanities |N/A |none | 0|acc | 0.5545|± |0.1585| | - other |N/A |none | 0|acc | 0.6823|± |0.1122| | - social_sciences|N/A |none | 0|acc | 0.7062|± |0.0825| | - stem |N/A |none | 0|acc | 0.5195|± |0.1231| |truthfulqa |N/A |none | 0|acc | 0.5058|± |0.0023| | | |none | 0|bleu_max |25.2659|± |0.7944| | | |none | 0|bleu_acc | 0.5557|± |0.0174| | | |none | 0|bleu_diff | 4.5134|± |0.7505| | | |none | 0|rouge1_max |51.5877|± |0.8677| | | |none | 0|rouge1_acc | 0.5496|± |0.0174| | | |none | 0|rouge1_diff| 6.8850|± |1.0155| | | |none | 0|rouge2_max |36.0848|± |1.0385| | | |none | 0|rouge2_acc | 0.4700|± |0.0175| | | |none | 0|rouge2_diff| 5.8893|± |1.1296| | | |none | 0|rougeL_max |48.4591|± |0.8901| | | |none | 0|rougeL_acc | 0.5496|± |0.0174| | | |none | 0|rougeL_diff| 6.5791|± |1.0249| ``` ## 🧩 Configuration ```yaml slices: - sources: - model: mistralai/Mistral-7B-Instruct-v0.2 layer_range: [0, 32] - model: mlabonne/NeuralHermes-2.5-Mistral-7B layer_range: [0, 32] merge_method: slerp base_model: mistralai/Mistral-7B-Instruct-v0.2 parameters: t: - filter: self_attn value: [0, 0.5, 0.3, 0.7, 1] - filter: mlp value: [1, 0.5, 0.7, 0.3, 0] - value: 0.5 dtype: bfloat16 ``` ## 💻 Usage ```python !pip install -qU transformers accelerate from transformers import AutoTokenizer import transformers import torch model = "MaziyarPanahi/NeuralHermes-2.5-Mistral-7B-Mistral-7B-Instruct-v0.2-slerp" 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"]) ```