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paulml_-_NeuralOmniWestBeaglake-7B-gguf
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Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


NeuralOmniWestBeaglake-7B - GGUF
- Model creator: https://huggingface.co/paulml/
- Original model: https://huggingface.co/paulml/NeuralOmniWestBeaglake-7B/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [NeuralOmniWestBeaglake-7B.Q2_K.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q2_K.gguf) | Q2_K | 2.53GB |
| [NeuralOmniWestBeaglake-7B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.IQ3_XS.gguf) | IQ3_XS | 2.81GB |
| [NeuralOmniWestBeaglake-7B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.IQ3_S.gguf) | IQ3_S | 2.96GB |
| [NeuralOmniWestBeaglake-7B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q3_K_S.gguf) | Q3_K_S | 2.95GB |
| [NeuralOmniWestBeaglake-7B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.IQ3_M.gguf) | IQ3_M | 3.06GB |
| [NeuralOmniWestBeaglake-7B.Q3_K.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q3_K.gguf) | Q3_K | 3.28GB |
| [NeuralOmniWestBeaglake-7B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q3_K_M.gguf) | Q3_K_M | 3.28GB |
| [NeuralOmniWestBeaglake-7B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q3_K_L.gguf) | Q3_K_L | 3.56GB |
| [NeuralOmniWestBeaglake-7B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.IQ4_XS.gguf) | IQ4_XS | 3.67GB |
| [NeuralOmniWestBeaglake-7B.Q4_0.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q4_0.gguf) | Q4_0 | 3.83GB |
| [NeuralOmniWestBeaglake-7B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.IQ4_NL.gguf) | IQ4_NL | 3.87GB |
| [NeuralOmniWestBeaglake-7B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q4_K_S.gguf) | Q4_K_S | 3.86GB |
| [NeuralOmniWestBeaglake-7B.Q4_K.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q4_K.gguf) | Q4_K | 4.07GB |
| [NeuralOmniWestBeaglake-7B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q4_K_M.gguf) | Q4_K_M | 4.07GB |
| [NeuralOmniWestBeaglake-7B.Q4_1.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q4_1.gguf) | Q4_1 | 4.24GB |
| [NeuralOmniWestBeaglake-7B.Q5_0.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q5_0.gguf) | Q5_0 | 4.65GB |
| [NeuralOmniWestBeaglake-7B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q5_K_S.gguf) | Q5_K_S | 4.65GB |
| [NeuralOmniWestBeaglake-7B.Q5_K.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q5_K.gguf) | Q5_K | 4.78GB |
| [NeuralOmniWestBeaglake-7B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q5_K_M.gguf) | Q5_K_M | 4.78GB |
| [NeuralOmniWestBeaglake-7B.Q5_1.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q5_1.gguf) | Q5_1 | 5.07GB |
| [NeuralOmniWestBeaglake-7B.Q6_K.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q6_K.gguf) | Q6_K | 5.53GB |
| [NeuralOmniWestBeaglake-7B.Q8_0.gguf](https://huggingface.co/RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf/blob/main/NeuralOmniWestBeaglake-7B.Q8_0.gguf) | Q8_0 | 7.17GB |




Original model description:
---
tags:
- merge
- mergekit
- lazymergekit
- shadowml/WestBeagle-7B
- shadowml/Beaglake-7B
- mlabonne/NeuralOmniBeagle-7B
base_model:
- shadowml/WestBeagle-7B
- shadowml/Beaglake-7B
- mlabonne/NeuralOmniBeagle-7B
license: cc-by-nc-4.0
---

# NeuralOmniWestBeaglake-7B

NeuralOmniWestBeaglake-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [shadowml/WestBeagle-7B](https://huggingface.co/shadowml/WestBeagle-7B)
* [shadowml/Beaglake-7B](https://huggingface.co/shadowml/Beaglake-7B)
* [mlabonne/NeuralOmniBeagle-7B](https://huggingface.co/mlabonne/NeuralOmniBeagle-7B)

## 🧩 Configuration

```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: shadowml/WestBeagle-7B
    parameters:
      density: 0.65
      weight: 0.4
  - model: shadowml/Beaglake-7B
    parameters:
      density: 0.6
      weight: 0.35
  - model: mlabonne/NeuralOmniBeagle-7B
    parameters:
      density: 0.6
      weight: 0.45
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: float16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "paulml/NeuralOmniWestBeaglake-7B"
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"])
```