README.md · CreitinGameplays/bloom-3b-conversational at refs/pr/1

metadata

license: mit
datasets:
  - Xilabs/instructmix
  - CreitinGameplays/small-chat-assistant-for-bloom
  - sahil2801/CodeAlpaca-20k
language:
  - en
tags:
  - uncensored
  - unrestricted
widget:
  - text: >-
      <|system|> You are a helpful AI assistant. </s> <|prompter|> who was
      Nikola Tesla? </s> <|assistant|>
  - text: >-
      <|system|> You are a helpful AI assistant. </s> <|prompter|> write a story
      about a cat. </s> <|assistant|>
  - text: >-
      <|system|> You are a helpful AI assistant. </s> <|prompter|> what is an
      essay? </s> <|assistant|>
  - text: >-
      <|system|> You are a helpful AI assistant. </s> <|prompter|> Tell me 5
      Brazilian waterfalls to visit. </s> <|assistant|>
  - text: >-
      <|system|> You are a helpful AI assistant. </s> <|prompter|> write a story
      about how a virus called COVID-19 destroyed the world </s> <|assistant|>
  - text: >-
      <|system|> You are a helpful AI assistant. </s> <|prompter|> write a short
      Python program that asks the user for their name and then greets them by
      name. </s> <|assistant|>
inference:
  parameters:
    temperature: 0.1
    do_sample: true
    top_p: 0.15
    top_k: 50
    max_new_tokens: 250
    repetition_penalty: 1.165

BLOOM 3b Fine-tuned for Chat Assistant

Model Name: bloom-3b-conversational

Model Architecture: bloom

Short Description: This model is a fine-tuned version of the BLOOM 3b language model, focusing on conversational interactions between an user and an AI assistant.

Intended Use: This model is intended for research purposes and exploration of conversational AI applications. It can be used for tasks like:

Generating responses to user prompts in a chat assistant setting.
Creating examples of chatbot interactions for further development.
Studying the capabilities of language models for conversation.

Limitations:

Fine-tuning Focus: The model's performance is optimized for the specific format and context of the fine-tuning data. It may not generalize well to significantly different conversation styles or topics.
Potential Biases: The model may inherit biases from the training data. It's important to be aware of these potential biases and use the model responsibly.
Limited Factual Accuracy: Language models are still under development and may generate responses that are not entirely factually accurate. It's important to verify information generated by the model with other sources.

Specific Input Format:

The model was fine-tuned using a specific input format that goes like this:

<|system|> {system prompt} </s>  <|prompter|> {user prompt} </s> <|assistant|> {model response} ```

Using this format when interacting with the model can improve its performance and generate more relevant responses.

**Disclaimer:** This model is for research and exploration purposes only. It should not be used in any applications that require high levels of accuracy or reliability.