metadata

license: apache-2.0
language:
  - en

Model Card: kevin009/lamatama

Model Description

The kevin009/lamatama model is a groundbreaking achievement in the field of language modeling, showcasing the power of leveraging a substantial dataset and state-of-the-art training techniques. This model is designed to push the boundaries of what's possible in natural language understanding and generation.

Training Details

Model Architecture: The kevin009/lamatama model is built upon the architecture and tokenizer of Llama 2, ensuring compatibility and easy integration with various open-source projects.
Dataset: It was pretrained on an impressive 3 trillion tokens, a scale that allows for a deep and nuanced understanding of language.
Training Period: The training process was carried out over 90 days, utilizing 16 A100-40G GPUs, a testament to the model's efficiency and the team's optimization skills.

Fine-tuning

This specific version of the model has been fine-tuned to excel in chat-based applications. It builds upon the TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T model, incorporating learnings and optimizations from HF's Zephyr's training recipe.

Initial Phase: The model was first fine-tuned on a variant of the UltraChat dataset, which is rich in synthetic dialogues generated by ChatGPT.
Further Alignment: Subsequent alignment was achieved using 🤗 TRL's DPOTrainer with the openbmb/UltraFeedback dataset, comprising 64k prompts and model completions ranked by GPT-4.

How to Use

Ensure you have transformers>=4.34. For detailed instructions and updates, check out the GitHub page for kevin009/lamatama.

Installation (for versions <= v4.34)

pip install git+https://github.com/huggingface/transformers.git
pip install accelerate

Example Usage

Here's a quick guide on using kevin009/lamatama for generating text:

import torch
from transformers import pipeline

# Initialize the pipeline
pipe = pipeline("text-generation", model="kevin009/lamatama", torch_dtype=torch.bfloat16, device_map="auto")

# Sample dialogue with templating
messages = [
    {"role": "system", "content": "You are a friendly chatbot who always responds in the style of a pirate"},
    {"role": "user", "content": "How many helicopters can a human eat in one sitting?"}
]

# Generate prompt and outputs
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

Acknowledgements

This model is a product of collaboration and innovative approaches to language modeling. We extend our thanks to all contributors, as well as the creators of the datasets and training methodologies that made kevin009/lamatama a reality.

This model card introduces kevin009/lamatama, a versatile and powerful language model fine-tuned for chat applications, demonstrating exceptional understanding and generation capabilities.