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Adding Evaluation Results (#1)
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metadata
language:
  - ta
  - en
license: llama2
model-index:
  - name: tamil-llama-13b-instruct-v0.1
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 54.52
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abhinand/tamil-llama-13b-instruct-v0.1
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 79.35
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abhinand/tamil-llama-13b-instruct-v0.1
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 50.37
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abhinand/tamil-llama-13b-instruct-v0.1
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 41.22
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abhinand/tamil-llama-13b-instruct-v0.1
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 76.56
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abhinand/tamil-llama-13b-instruct-v0.1
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 7.51
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=abhinand/tamil-llama-13b-instruct-v0.1
          name: Open LLM Leaderboard

Tamil LLaMA 13B Instruct v0.1

Welcome to the inaugural release of the Tamil LLaMA 13B instruct model – an important step in advancing LLMs for the Tamil language. This model is ready for immediate inference and is also primed for further fine-tuning to cater to your specific NLP tasks.

To dive deep into the development and capabilities of this model, please read the research paper and the introductory blog post (WIP) that outlines our journey and the model's potential impact.

Model description

The Tamil LLaMA models have been enhanced and tailored specifically with an extensive Tamil vocabulary of 16,000 tokens, building upon the foundation set by the original LLaMA-2.

Prompting Format

Prompt Template Without Input

{system_prompt}

### Instruction:
{instruction or query}

### Response:
{response}

Prompt Template With Input

{system_prompt}

### Instruction:
{instruction or query}

### Input:
{input}

### Response:
{response}

Related Models

Model Type Data Base Model # Params Download Links
Tamil LLaMA 7B Base Base model 12GB LLaMA 7B 7B HF Hub
Tamil LLaMA 13B Base Base model 4GB LLaMA 13B 13B HF Hub
Tamil LLaMA 7B Instruct Instruction following model 145k instructions Tamil LLaMA 7B Base 7B HF Hub
Tamil LLaMA 13B Instruct Instruction following model 145k instructions Tamil LLaMA 13B Base 13B HF Hub

Usage Note

It's important to note that the models have not undergone detoxification. Therefore, while they possess impressive linguistic capabilities, there is a possibility for them to generate content that could be deemed harmful or offensive. We urge users to exercise discretion and supervise the model's outputs closely, especially in public or sensitive applications.

Meet the Developers

Get to know the creators behind this innovative model and follow their contributions to the field:

Citation

If you use this model or any of the the Tamil-Llama datasets in your research, please cite:

@misc{balachandran2023tamilllama,
      title={Tamil-Llama: A New Tamil Language Model Based on Llama 2}, 
      author={Abhinand Balachandran},
      year={2023},
      eprint={2311.05845},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

We hope this model serves as a valuable tool in your NLP toolkit and look forward to seeing the advancements it will enable in the understanding and generation of the Tamil language.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 51.59
AI2 Reasoning Challenge (25-Shot) 54.52
HellaSwag (10-Shot) 79.35
MMLU (5-Shot) 50.37
TruthfulQA (0-shot) 41.22
Winogrande (5-shot) 76.56
GSM8k (5-shot) 7.51