RichardErkhov/paulml_-_NeuralOmniWestBeaglake-7B-gguf

Quantization made by Richard Erkhov.

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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	Q2_K	2.53GB
NeuralOmniWestBeaglake-7B.IQ3_XS.gguf	IQ3_XS	2.81GB
NeuralOmniWestBeaglake-7B.IQ3_S.gguf	IQ3_S	2.96GB
NeuralOmniWestBeaglake-7B.Q3_K_S.gguf	Q3_K_S	2.95GB
NeuralOmniWestBeaglake-7B.IQ3_M.gguf	IQ3_M	3.06GB
NeuralOmniWestBeaglake-7B.Q3_K.gguf	Q3_K	3.28GB
NeuralOmniWestBeaglake-7B.Q3_K_M.gguf	Q3_K_M	3.28GB
NeuralOmniWestBeaglake-7B.Q3_K_L.gguf	Q3_K_L	3.56GB
NeuralOmniWestBeaglake-7B.IQ4_XS.gguf	IQ4_XS	3.67GB
NeuralOmniWestBeaglake-7B.Q4_0.gguf	Q4_0	3.83GB
NeuralOmniWestBeaglake-7B.IQ4_NL.gguf	IQ4_NL	3.87GB
NeuralOmniWestBeaglake-7B.Q4_K_S.gguf	Q4_K_S	3.86GB
NeuralOmniWestBeaglake-7B.Q4_K.gguf	Q4_K	4.07GB
NeuralOmniWestBeaglake-7B.Q4_K_M.gguf	Q4_K_M	4.07GB
NeuralOmniWestBeaglake-7B.Q4_1.gguf	Q4_1	4.24GB
NeuralOmniWestBeaglake-7B.Q5_0.gguf	Q5_0	4.65GB
NeuralOmniWestBeaglake-7B.Q5_K_S.gguf	Q5_K_S	4.65GB
NeuralOmniWestBeaglake-7B.Q5_K.gguf	Q5_K	4.78GB
NeuralOmniWestBeaglake-7B.Q5_K_M.gguf	Q5_K_M	4.78GB
NeuralOmniWestBeaglake-7B.Q5_1.gguf	Q5_1	5.07GB
NeuralOmniWestBeaglake-7B.Q6_K.gguf	Q6_K	5.53GB
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:

• shadowml/WestBeagle-7B
• shadowml/Beaglake-7B
• mlabonne/NeuralOmniBeagle-7B

🧩 Configuration

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

!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"])