Babylona_v0.1_GGUF

---

🧩 Configuration

models:
  - model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: FPHam/Writing_Partner_Mistral_7B
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
merge_method: ties
base_model: NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
parameters:
  normalize: true
  int8_mask: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "hvsq/Babylona_v0.1"
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"])