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RichardErkhov/Yuma42_-_KangalKhan-PressurizedRuby-7B-gguf

sourceHugging Faceupdated 2y agoView on Hugging Face
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KangalKhan-PressurizedRuby-7B - GGUF

  • —Model creator: https://huggingface.co/Yuma42/
  • —Original model: https://huggingface.co/Yuma42/KangalKhan-PressurizedRuby-7B/

Original model description: --- tags:

  • —merge
  • —mergekit
  • —lazymergekit
  • —Yuma42/KangalKhan-RawRuby-7B
  • —Yuma42/KangalKhan-Ruby-7B-Fixed base_model:
  • —Yuma42/KangalKhan-RawRuby-7B
  • —Yuma42/KangalKhan-Ruby-7B-Fixed license: apache-2.0 language:
  • —en ---

KangalKhan-PressurizedRuby-7B

KangalKhan-PressurizedRuby-7B is a merge of the following models using LazyMergekit:

🧩 Configuration

yaml
models:
  - model: teknium/OpenHermes-2.5-Mistral-7B
    # no parameters necessary for base model
  - model: Yuma42/KangalKhan-RawRuby-7B
    parameters:
      density: 0.6
      weight: 0.5
  - model: Yuma42/KangalKhan-Ruby-7B-Fixed
    parameters:
      density: 0.6
      weight: 0.5
merge_method: ties
base_model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
  normalize: true
dtype: bfloat16

💻 Usage

python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Yuma42/KangalKhan-PressurizedRuby-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"])