--- license: apache-2.0 tags: - merge - mergekit - lazymergekit - OpenPipe/mistral-ft-optimized-1227 - mlabonne/NeuralHermes-2.5-Mistral-7B base_model: - OpenPipe/mistral-ft-optimized-1227 - mlabonne/NeuralHermes-2.5-Mistral-7B --- # NeuralPipe-7B-slerp-v0.2 NeuralPipe-7B-slerp-v0.2 is a merge of the following models: * [OpenPipe/mistral-ft-optimized-1227](https://huggingface.co/OpenPipe/mistral-ft-optimized-1227) * [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 | 0.7554|± |0.0406| | | |none | 0|acc_norm | 0.7573|± |0.0332| |mmlu |N/A |none | 0|acc | 0.6188|± |0.1472| | - humanities |N/A |none | 0|acc | 0.5645|± |0.1686| | - other |N/A |none | 0|acc | 0.6987|± |0.1098| | - social_sciences|N/A |none | 0|acc | 0.7215|± |0.0887| | - stem |N/A |none | 0|acc | 0.5208|± |0.1392| |truthfulqa |N/A |none | 0|acc | 0.4746|± |0.0024| | | |none | 0|bleu_max |26.7118|± |0.8092| | | |none | 0|bleu_acc | 0.4957|± |0.0175| | | |none | 0|bleu_diff | 3.1016|± |0.8065| | | |none | 0|rouge1_max |53.1171|± |0.8499| | | |none | 0|rouge1_acc | 0.5055|± |0.0175| | | |none | 0|rouge1_diff| 4.0629|± |1.0345| | | |none | 0|rouge2_max |39.1331|± |1.0068| | | |none | 0|rouge2_acc | 0.4492|± |0.0174| | | |none | 0|rouge2_diff| 3.7457|± |1.1652| | | |none | 0|rougeL_max |49.8547|± |0.8818| | | |none | 0|rougeL_acc | 0.5006|± |0.0175| | | |none | 0|rougeL_diff| 3.6422|± |1.0540| ``` ## 🧩 Configuration ```yaml slices: - sources: - model: OpenPipe/mistral-ft-optimized-1227 layer_range: [0, 32] - model: mlabonne/NeuralHermes-2.5-Mistral-7B layer_range: [0, 32] merge_method: slerp base_model: OpenPipe/mistral-ft-optimized-1227 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/NeuralPipe-7B-slerp-v0.2" 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"]) ```