upon sseing the eval bechmarks on the LLM Leaderboard, this is the best performing model, but it's not uncensored, and it's answers are not really good when chatting with it. I will further train it one datasets like dolphin and other.

json

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}

🧩 Configuration

yaml

slices:
  - sources:
      - model: Locutusque/Hercules-3.1-Mistral-7B
        layer_range: [0, 32]
      - model: cognitivecomputations/dolphin-2.8-experiment26-7b
        layer_range: [0, 32]
merge_method: slerp
base_model: Locutusque/Hercules-3.1-Mistral-7B
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Isaak-Carter/JOSIE_Beta-3-7B-slerp"
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"])

Goekdeniz-Guelmez/J.O.S.I.E.3-Beta3-slerp

JOSIE_Beta-3-7B-slerp

IMPORTANT!!!

🧩 Configuration

💻 Usage

Goekdeniz-Guelmez/
J.O.S.I.E.3-Beta3-slerp