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shwars/fido-rugpt3-small
fido-rugpt3-small is a text generation model from shwars. Use it when you need the model to write or continue text. It is set up for transformers.
FIDONet is a historic computer network based on nightly mail exchange between servers via telephone lines, which was popular in 1990-s. In FIDONet Cybernetic Immortality Project we are looking to create exhibits that…
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From the Hugging Face model README
FIDONet is a historic computer network based on nightly mail exchange between servers via telephone lines, which was popular in 1990-s. In FIDONet Cybernetic Immortality Project we are looking to create exhibits that will revive now-almost-dead FIDONet by automatically writing correspondence in FIDONet style via generative large language models.
This model allows post generation in Russian Language. If you are looking for English-language version of Fido-GPT, take a look at fido-gpt model.
This model is based on ruGPT3-small model, and was fine-tuned for 1 epoch on subset of selected fidonet archives from 2013-2015. The following echo areas were included: ru.anekdot, ru.anekdot.digest, ru.anekdot.filtered, ru.anekdot.talks, ru.anekdot.the.best, ru.computer.humor, ru.cpp, ru.dos, ru.film, ru.java, ru.linguist, ru.linux, ru.moderator, ru.pascal, ru.photo, ru.physics, ru.psychology.
Total training dataset size was 552 Mb. The process took around 3 hours on NVidia V100 compute in Yandex Datasphere service.
This code can be used for generation:
from transformers import pipeline, AutoModelForCausalLM,AutoTokenizer
import torch
model_name = 'shwars/fido-rugpt3-small'
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
pipe = pipeline(model=model,tokenizer=tokenizer,task="text-generation",device="cuda")
result = pipe("<s>Area: ru.anekdot",do_sample=True,max_length=500)[0]['generated_text'].replace('\\n','\n')
Project idea and model training: Dmitry Soshnikov