--- license: apache-2.0 language: - en --- # NeuralMaxime-7B-slerp-GGUF ## Description This repo contains GGUF format model files for NeuralMaxime-7B-slerp-GGUF. ## Files Provided | Name | Quant | Bits | File Size | Remark | | --------------------------------- | ------ | ---- | --------- | -------------------------------- | | neuralmaxime-7b-slerp.IQ3_S.gguf | IQ3_S | 3 | 3.18 GB | 3.44 bpw quantization | | neuralmaxime-7b-slerp.IQ3_M.gguf | IQ3_M | 3 | 3.28 GB | 3.66 bpw quantization mix | | neuralmaxime-7b-slerp.Q4_0.gguf | Q4_0 | 4 | 4.11 GB | 3.56G, +0.2166 ppl | | neuralmaxime-7b-slerp.IQ4_NL.gguf | IQ4_NL | 4 | 4.16 GB | 4.25 bpw non-linear quantization | | neuralmaxime-7b-slerp.Q4_K_M.gguf | Q4_K_M | 4 | 4.37 GB | 3.80G, +0.0532 ppl | | neuralmaxime-7b-slerp.Q5_K_M.gguf | Q5_K_M | 5 | 5.13 GB | 4.45G, +0.0122 ppl | | neuralmaxime-7b-slerp.Q6_K.gguf | Q6_K | 6 | 5.94 GB | 5.15G, +0.0008 ppl | | neuralmaxime-7b-slerp.Q8_0.gguf | Q8_0 | 8 | 7.70 GB | 6.70G, +0.0004 ppl | ## Parameters | path | type | architecture | rope_theta | sliding_win | max_pos_embed | | ----------------------------- | ------- | ------------------ | ---------- | ----------- | ------------- | | Kukedlc/NeuralMaxime-7B-slerp | mistral | MistralForCausalLM | 10000.0 | 4096 | 32768 | ## Benchmarks ![](https://i.ibb.co/g7sqr1r/Neural-Maxime-7-B-slerp.png) # Original Model Card --- tags: - merge - mergekit - lazymergekit - mlabonne/AlphaMonarch-7B - mlabonne/NeuralMonarch-7B base_model: - mlabonne/AlphaMonarch-7B - mlabonne/NeuralMonarch-7B license: apache-2.0 --- # NeuralMaxime-7B-slerp ![](https://raw.githubusercontent.com/kukedlc87/imagenes/main/DALL%C2%B7E%202024-02-18%2015.45.07%20-%20Visualize%20a%20highly%20sophisticated%2C%20high-definition%20robot%20named%20Neural%20Maxime.%20This%20language%20model%20robot%20is%20distinguished%20by%20its%20innovative%20design%2C%20feat.webp) NeuralMaxime-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B) * [mlabonne/NeuralMonarch-7B](https://huggingface.co/mlabonne/NeuralMonarch-7B) ## 🧩 Configuration ```yaml slices: - sources: - model: mlabonne/AlphaMonarch-7B layer_range: [0, 32] - model: mlabonne/NeuralMonarch-7B layer_range: [0, 32] merge_method: slerp base_model: mlabonne/AlphaMonarch-7B 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 = "Kukedlc/NeuralMaxime-7B-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"]) ```