Quantization made by Richard Erkhov.
This model can be used for text generation.
Significant research has explored bias and fairness issues with language models (see, e.g.,
Sheng et al. (2021) and
Bender et al. (2021) ).
Hebrew Wikipedia Dump (hewiki abstract) from May 2020
This model was fined tuned upon
hebrew-gpt_neo-tiny which was previously trained using
EleutherAI's gpt-neo .
Fine-tuning on the wiki-absract text was done using
@minimaxir 's
aitextgen .
Model configs for the hebrew-gpt_neo-tiny is available on the
hebrew-gpt_neo model github Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019) . We present the hardware type based on the
associated paper .
Hardware Type: [More information needed]
Hours used: Unknown
Cloud Provider: GCP tpu-v8s
Compute Region: europe-west4
Carbon Emitted: [More information needed]
A Google Colab Notebook is also available
here from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Norod78/hebrew-bad_wiki-gpt_neo-tiny")
model = AutoModelForCausalLM.from_pretrained("Norod78/hebrew-bad_wiki-gpt_neo-tiny")
