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NeuralMaxime-7B-slerp-GGUF

GGUF
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mlabonne/AlphaMonarch-7B
mlabonne/NeuralMonarch-7B
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NeuralMaxime-7B-slerp-GGUF
File size: 3,643 Bytes 
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---
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-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_XXS.gguf | IQ3_XXS |  3   |  3.02 GB  | 3.06 bpw quantization            |
| 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

# 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"])
```