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--- |
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license: mit |
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datasets: |
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- VishnuPJ/Malayalam_CultureX_IndicCorp_SMC |
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library_name: transformers |
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language: |
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- ml |
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tags: |
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- mamba |
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- ssm |
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- s6 |
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- jamba |
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- llm |
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- state space models |
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- malayalam |
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- indic |
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--- |
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# Ma-layala-mba |
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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. |
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## Model Description |
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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. |
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- **Model Type**: A 128M Jamba model finetuned on ~1.5M samples of Malayalam prompt-response pairs from a subset of the IndicCorop Dataset |
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- **Language(s)**: Malayalam |
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- **License**: GNU General Public License v3.0 |
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- **Training Precision**: bfloat16 |
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## Example Usage |
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Here's a quick example to get you started with the Ma-layala-mba model: |
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```python |
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from transformers import MaLayalaMbaForCausalLM, AutoTokenizer, pipeline |
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model = MaLayalaMbaForCausalLM.from_pretrained( |
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"aoxo/Ma-layala-mba_Tiny_128M", |
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# load_in_8bit=True, # Set this depending on the GPU you have |
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torch_dtype=torch.bfloat16, |
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device_map={"": 0}, # Set this depending on the number of GPUs you have |
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local_files_only=False # Optional |
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) |
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model.eval() |
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tokenizer = AutoTokenizer.from_pretrained("aoxo/Ma-layala-mba_Tiny_128M") |
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input_ids = tokenizer("മലയാളം പര്യായപദങ്ങളിൽ ഒരു പരീക്ഷ പേപ്പർ ഉണ്ടാക്കുക", return_tensors='pt').to(model.device)["input_ids"] |
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outputs = model.generate(input_ids, max_new_tokens=100) |
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print(tokenizer.batch_decode(outputs)) |
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``` |
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### Example Output: |
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``` |
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മലയാളം പര്യായപദങ്ങളിൽ ഒരു പരീക്ഷ പേപ്പർ ഉണ്ടാക്കുക |
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a. വലിയ - __________ |
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b. രസം - __________ |
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c. സുഖം - __________ |
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d. പ്രകാശം - __________ |
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e. വേഗം - __________ |
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``` |
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## Usage Note |
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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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## Meet the Developers |
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- **Alosh Denny** |
