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Llama3_8B_Odia_Unsloth is a fine-tuned Odia large language model with 8 billion parameters, and it is based on Llama3. The model is fine-tuned on a comprehensive 171k Odia instruction set, encompassing domain-specific and cultural nuances.

The fine-tuning process leverages Unsloth, expediting the training process for optimal efficiency.

For more details about the model, data, training procedure, and evaluations, go through the blog post.

Model Description

  • Model type: A 8B fine-tuned model
  • Primary Language(s): Odia and English
  • License: Llama3


Sample inference script.


#Install Unsloth
import torch
major_version, minor_version = torch.cuda.get_device_capability()
# Must install separately since Colab has torch 2.2.1, which breaks packages
!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
if major_version >= 8:
    # Use this for new GPUs like Ampere, Hopper GPUs (RTX 30xx, RTX 40xx, A100, H100, L40)
    !pip install --no-deps packaging ninja einops flash-attn xformers trl peft accelerate bitsandbytes
    # Use this for older GPUs (V100, Tesla T4, RTX 20xx)
    !pip install --no-deps xformers trl peft accelerate bitsandbytes

Model loading

from unsloth import FastLanguageModel
import torch
max_seq_length = 2048 
dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name = "OdiaGenAI-LLM/Llama3_8B_Odia_Unsloth",
    max_seq_length = max_seq_length,
    dtype = dtype,
    load_in_4bit = load_in_4bit,

alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:

### Input:

### Response:


inputs = tokenizer(
        "କୋଭିଡ୍ 19 ର ଲକ୍ଷଣଗୁଡ଼ିକ କ’ଣ?", # instruction
        "", # input
        "", # output - leave this blank for generation!
], return_tensors = "pt").to("cuda")

outputs = model.generate(**inputs, max_new_tokens = 512, use_cache = True)

Citation Information

If you find this model useful, please consider giving 👏 and citing:

  author = {Shantipriya Parida and Sambit Sekhar and Debasish Dhal and Shakshi Panwar},
  title = {OdiaGenAI Releases Llama3 Fine-tuned Model for the Odia Language},
  year = {2024},
  publisher = {Hugging Face},
  journal = {Hugging Face repository},
  howpublished = {\url{https://huggingface.co/OdiaGenAI}},


  • Dr.Shantipriya Parida
  • Sambit Sekhar
  • Debasish Dhal
  • Shakshi Panwar
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8.03B params
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