Ma-layala-mba
Welcome to Ma-layala-mba, a base Indic language model designed to push the boundaries of NLP for Indian languages. It is based on the Mamba series of state space models.
Model Description
Ma-layala-mba is a state-of-the-art S6 SSM model specifically crafted for the South Indian regional and state language of Kerala: Malayalam. It integrates traditional Attention mechanisms with innovative approaches such as MLPs and State Space Models (SSMs) to handle complex linguistic features and achieve high accuracy in language understanding and generation.
- Model Type: A 128M Jamba model finetuned on ~1 million samples of Malayalam prompt-response pairs from a subset of the IndicCorp Dataset
- Language(s): Malayalam
- License: GNU General Public License v3.0
- Training Precision: bfloat16
Example Usage
Here's a quick example to get you started with the Ma-layala-mba model:
from transformers import MaLayalaMbaForCausalLM, AutoTokenizer, pipeline
model = MaLayalaMbaForCausalLM.from_pretrained(
"aoxo/Ma-layala-mba_Tiny_128M",
# load_in_8bit=True, # Set this depending on the GPU you have
torch_dtype=torch.bfloat16,
device_map={"": 0}, # Set this depending on the number of GPUs you have
local_files_only=False # Optional
)
model.eval()
tokenizer = AutoTokenizer.from_pretrained("aoxo/Ma-layala-mba_Tiny_128M")
input_ids = tokenizer("മലയാളം പര്യായപദങ്ങളിൽ ഒരു പരീക്ഷ പേപ്പർ ഉണ്ടാക്കുക", return_tensors='pt').to(model.device)["input_ids"]
outputs = model.generate(input_ids, max_new_tokens=100)
print(tokenizer.batch_decode(outputs))
Example Output:
മലയാളം പര്യായപദങ്ങളിൽ ഒരു പരീക്ഷ പേപ്പർ ഉണ്ടാക്കുക
a. വലിയ - __________
b. രസം - __________
c. സുഖം - __________
d. പ്രകാശം - __________
e. വേഗം - __________
Usage Note
Please be aware that this model has not undergone comprehensive detoxification or censorship. While it exhibits strong linguistic capabilities, there is a possibility of generating content that may be deemed harmful or offensive. We advise users to apply discretion and closely monitor the model's outputs, especially in public or sensitive settings.
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