metadata

license: apache-2.0
language:
  - en
datasets:
  - Intel/orca_dpo_pairs

Model based on mindy-labs/mindy-7b-v2 (downstream version of Mistral7B) finetuned using Direct Preference Optimization on Intel/orca_dpo_pairs.

How to use

You can use this model directly with a pipeline for sentiment-analysis:

from transformers import pipeline

messages = [
    {
      "role": "system",
      "content": "You are a friendly chatbot who always responds in the style of a pirate."
    },
    {
      "role": "user",
      "content": "What is the capital city of France?"
    }
]
pipe = pipeline("conversational", "bardsai/jaskier-7b-dpo")
print(pipe(messages))

assistant: In me hearties, th' capital city o' France be called Paris! A grand an' beautiful port full o' culture an' history. Yar, it be a fine place to visit an' swashbuckle abou'

Generate text

sequences = pipeline( prompt, do_sample=True, temperature=0.7, top_p=0.9, num_return_sequences=1, max_length=300, )

print(sequences[0]['generated_text'])


## Changelog

- 2023-01-10: Initial release

## About bards.ai

At bards.ai, we focus on providing machine learning expertise and skills to our partners, particularly in the areas of nlp, machine vision and time series analysis. Our team is located in Wroclaw, Poland. Please visit our website for more information: bards.ai

Let us know if you use our model :). Also, if you need any help, feel free to contact us at info@bards.ai