Maral

Description
Maral is a general-purpose generative language model that demonstrates excellent performance in tasks such as summarization and question-answering, specifically in the Russian language. Its advanced capabilities allow it to generate coherent and contextually accurate responses, making it highly effective for a wide range of natural language processing applications.
๐จโ๐ป Examples of usage
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("MadShift/Maral")
model = AutoModelForCausalLM.from_pretrained("MadShift/Maral", device_map="auto")
input_text = "ะะฒะตะดะธัะต ัะฒะพะน ัะตะบัั ะทะดะตัั"
input_ids = tokenizer(input_text, return_tensors="pt").to(model.device)
outputs = model.generate(**input_ids, max_new_tokens=256)
print(tokenizer.decode(outputs[0]))
- Downloads last month
- 6
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.