README.md

metadata

license: apache-2.0
tags:
  - merge
  - mergekit
  - lazymergekit
  - sethuiyer/SynthIQ-7b
  - openchat/openchat-3.5-0106

Chikuma

Chikuma is a merge of the following models using LazyMergekit:

• sethuiyer/SynthIQ-7b
• openchat/openchat-3.5-0106

🧩 Configuration

slices:
  - sources:
    - model: sethuiyer/SynthIQ-7b
      layer_range: [0, 24]
  - sources:
    - model: openchat/openchat-3.5-0106
      layer_range: [8, 32]
merge_method: passthrough
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "sethuiyer/Chikuma"
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"])

A large language model is a type of artificial intelligence (AI) system that has been trained on a vast amount of text data to understand and generate human-like text.
These models are capable of tasks such as text generation, translation, summarization, and more. They have a vast vocabulary and contextual understanding of language, allowing them to generate coherent and relevant responses.
Examples of large language models include GPT-3, OpenAI's text-based model, and Google's BERT, which is designed for natural language understanding.