| Quantization made by Richard Erkhov. | |
| [Github](https://github.com/RichardErkhov) | |
| [Discord](https://discord.gg/pvy7H8DZMG) | |
| [Request more models](https://github.com/RichardErkhov/quant_request) | |
| GPT-Neo-2.7B-Picard - bnb 4bits | |
| - Model creator: https://huggingface.co/KoboldAI/ | |
| - Original model: https://huggingface.co/KoboldAI/GPT-Neo-2.7B-Picard/ | |
| Original model description: | |
| --- | |
| language: en | |
| license: mit | |
| --- | |
| # GPT-Neo 2.7B - Picard | |
| ## Model Description | |
| GPT-Neo 2.7B-Picard is a finetune created using EleutherAI's GPT-Neo 2.7B model. | |
| ## Training data | |
| The training data contains around 1800 ebooks, mostly in the sci-fi and fantasy genres. | |
| ### How to use | |
| You can use this model directly with a pipeline for text generation. This example generates a different sequence each time it's run: | |
| ```py | |
| >>> from transformers import pipeline | |
| >>> generator = pipeline('text-generation', model='mrseeker87/GPT-Neo-2.7B-Picard') | |
| >>> generator("Jean-Luc Picard", do_sample=True, min_length=50) | |
| [{'generated_text': 'Jean-Luc Picard, the captain of a Federation starship in command of one of Starfleet's few fulltime scientists.'}] | |
| ``` | |
| ### Limitations and Biases | |
| GPT-Neo was trained as an autoregressive language model. This means that its core functionality is taking a string of text and predicting the next token. While language models are widely used for tasks other than this, there are a lot of unknowns with this work. | |
| GPT-Neo was trained on the Pile, a dataset known to contain profanity, lewd, and otherwise abrasive language. Depending on your usecase GPT-Neo may produce socially unacceptable text. See Sections 5 and 6 of the Pile paper for a more detailed analysis of the biases in the Pile. | |
| As with all language models, it is hard to predict in advance how GPT-Neo will respond to particular prompts and offensive content may occur without warning. We recommend having a human curate or filter the outputs before releasing them, both to censor undesirable content and to improve the quality of the results. | |
| ### BibTeX entry and citation info | |
| The model is made using the following software: | |
| ```bibtex | |
| @software{gpt-neo, | |
| author = {Black, Sid and | |
| Leo, Gao and | |
| Wang, Phil and | |
| Leahy, Connor and | |
| Biderman, Stella}, | |
| title = {{GPT-Neo: Large Scale Autoregressive Language | |
| Modeling with Mesh-Tensorflow}}, | |
| month = mar, | |
| year = 2021, | |
| note = {{If you use this software, please cite it using | |
| these metadata.}}, | |
| publisher = {Zenodo}, | |
| version = {1.0}, | |
| doi = {10.5281/zenodo.5297715}, | |
| url = {https://doi.org/10.5281/zenodo.5297715} | |
| } | |
| ``` | |