Sauerkrautlm 7b HerO Mistral 7B Instruct V0.1

🚀 SauerkrautLM-7b-HerO-Mistral-7B-Instruct-v0.1

SauerkrautLM-7b-HerO-Mistral-7B-Instruct-v0.1 is a merged model that combines the strengths of multiple models. It offers enhanced text - generation capabilities, especially useful for various natural language processing tasks.

🚀 Quick Start

This model is a merge of the following two models:

• mistralai/Mistral-7B-Instruct-v0.1
• VAGOsolutions/SauerkrautLM-7b-HerO

📚 Documentation

🧩 Configuration

The following is the configuration for merging these models:

slices:
  - sources:
      - model: mistralai/Mistral-7B-Instruct-v0.1
        layer_range: [0, 32]
      - model: VAGOsolutions/SauerkrautLM-7b-HerO
        layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-Instruct-v0.1
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 Examples

Basic Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "MaziyarPanahi/SauerkrautLM-7b-HerO-Mistral-7B-Instruct-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"])

📄 License

This project is licensed under the Apache-2.0 license.