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RichardErkhov/
Kukedlc_-_NeuralKrishna-7B-v3-gguf

Name: Kukedlc_-_NeuralKrishna-7B-v3-gguf
Availability: InStock

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gguf

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Quantization made by Richard Erkhov.

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NeuralKrishna-7B-v3 - GGUF

Model creator: https://huggingface.co/Kukedlc/
Original model: https://huggingface.co/Kukedlc/NeuralKrishna-7B-v3/

Name	Quant method	Size
NeuralKrishna-7B-v3.Q2_K.gguf	Q2_K	2.53GB
NeuralKrishna-7B-v3.IQ3_XS.gguf	IQ3_XS	2.81GB
NeuralKrishna-7B-v3.IQ3_S.gguf	IQ3_S	2.96GB
NeuralKrishna-7B-v3.Q3_K_S.gguf	Q3_K_S	2.95GB
NeuralKrishna-7B-v3.IQ3_M.gguf	IQ3_M	3.06GB
NeuralKrishna-7B-v3.Q3_K.gguf	Q3_K	3.28GB
NeuralKrishna-7B-v3.Q3_K_M.gguf	Q3_K_M	3.28GB
NeuralKrishna-7B-v3.Q3_K_L.gguf	Q3_K_L	3.56GB
NeuralKrishna-7B-v3.IQ4_XS.gguf	IQ4_XS	3.67GB
NeuralKrishna-7B-v3.Q4_0.gguf	Q4_0	3.83GB
NeuralKrishna-7B-v3.IQ4_NL.gguf	IQ4_NL	3.87GB
NeuralKrishna-7B-v3.Q4_K_S.gguf	Q4_K_S	3.86GB
NeuralKrishna-7B-v3.Q4_K.gguf	Q4_K	4.07GB
NeuralKrishna-7B-v3.Q4_K_M.gguf	Q4_K_M	4.07GB
NeuralKrishna-7B-v3.Q4_1.gguf	Q4_1	4.24GB
NeuralKrishna-7B-v3.Q5_0.gguf	Q5_0	4.65GB
NeuralKrishna-7B-v3.Q5_K_S.gguf	Q5_K_S	4.65GB
NeuralKrishna-7B-v3.Q5_K.gguf	Q5_K	4.78GB
NeuralKrishna-7B-v3.Q5_K_M.gguf	Q5_K_M	4.78GB
NeuralKrishna-7B-v3.Q5_1.gguf	Q5_1	5.07GB
NeuralKrishna-7B-v3.Q6_K.gguf	Q6_K	5.53GB
NeuralKrishna-7B-v3.Q8_0.gguf	Q8_0	7.17GB

Original model description:

tags:

merge
mergekit
lazymergekit
Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT
Kukedlc/Fasciculus-Arcuatus-7B-slerp
Kukedlc/Neural4gsm8k base_model:
Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT
Kukedlc/Fasciculus-Arcuatus-7B-slerp
Kukedlc/Neural4gsm8k license: apache-2.0

NeuralKrishna-7B-v3

NeuralKrishna-7B-v3 is a merge of the following models using LazyMergekit:

🧩 Configuration

yaml

models:
  - model: mlabonne/Monarch-7B
    # no parameters necessary for base model
  - model: Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT
    parameters:
      density: 0.65
      weight: 0.36
  - model: Kukedlc/Fasciculus-Arcuatus-7B-slerp
    parameters:
      density: 0.6
      weight: 0.34
  - model: Kukedlc/Neural4gsm8k
    parameters:
      density: 0.6
      weight: 0.3
merge_method: dare_ties
base_model: mlabonne/Monarch-7B
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/NeuralKrishna-7B-v3"
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"])

RichardErkhov/Kukedlc_-_NeuralKrishna-7B-v3-gguf

Original model description:

NeuralKrishna-7B-v3

🧩 Configuration

💻 Usage

RichardErkhov/
Kukedlc_-_NeuralKrishna-7B-v3-gguf