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README.md
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---
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license: mit
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---
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# Ma-layala-mba
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from transformers import MaLayalaMbaForCausalLM, AutoTokenizer, pipeline
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model = MaLayalaMbaForCausalLM.from_pretrained(
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"aoxo/
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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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model.eval()
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tokenizer = AutoTokenizer.from_pretrained("aoxo/
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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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## Meet the Developers
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Get to know the creators behind Ma-layala-mba and follow their work:
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- **Alosh Denny**
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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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# Ma-layala-mba
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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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)
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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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## Meet the Developers
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- **Alosh Denny**
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