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--- |
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language: |
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- en |
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- kn |
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license: mit |
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tags: |
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- bilingual |
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- kannada |
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- english |
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metrics: |
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- accuracy |
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pipeline_tag: text-generation |
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model-index: |
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- name: Ambari-7B-base-v0.1-sharded |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 47.95 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fierysurf/Ambari-7B-base-v0.1-sharded |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 74.62 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fierysurf/Ambari-7B-base-v0.1-sharded |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 40.39 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fierysurf/Ambari-7B-base-v0.1-sharded |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 38.91 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fierysurf/Ambari-7B-base-v0.1-sharded |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 72.06 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fierysurf/Ambari-7B-base-v0.1-sharded |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 1.59 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fierysurf/Ambari-7B-base-v0.1-sharded |
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name: Open LLM Leaderboard |
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--- |
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(This repo contains the sharded version of the [original](https://huggingface.co/Cognitive-Lab/Ambari-7B-base-v0.1) Ambari-7B model) |
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# Ambari-7B-Base-v0.1 (sharded) |
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## Overview |
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Ambari-7B-Base-v0.1 is the first bilingual English/Kannada model in the Ambari series, developed and released by [Cognitivelab.in](https://www.cognitivelab.in/). Based on the Llama2 model by Meta, this 7B parameter model is the outcome of the pretraining stage, involving training on approximately 500 million new Kannada tokens. |
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## Usage |
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To use the Ambari-7B-Base-v0.1 model, you can follow the example code below: |
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```python |
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# Usage |
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import torch |
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from transformers import LlamaTokenizer, LlamaForCausalLM |
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model = LlamaForCausalLM.from_pretrained('Cognitive-Lab/Ambari-7B-Base-v0.1') |
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tokenizer = LlamaTokenizer.from_pretrained('Cognitive-Lab/Ambari-7B-Base-v0.1') |
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prompt = "ಕನ್ನಡದ ಇತಿಹಾಸವನ್ನು ವಿವರವಾಗಿ ತಿಳಿಸಿ" |
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inputs = tokenizer(prompt, return_tensors="pt") |
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# Generate |
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generate_ids = model.generate(inputs.input_ids, max_length=30) |
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decoded_output = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] |
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print(decoded_output) |
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``` |
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**Important:** The provided model serves as a foundation and is not designed for independent use. We strongly advise conducting finetuning tailored to your particular task(s) of interest before deploying it in a production environment. Feel free to customize the code according to your specific use case, ensuring that the model undergoes finetuning for optimal performance in your desired application. |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_fierysurf__Ambari-7B-base-v0.1-sharded) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |45.92| |
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|AI2 Reasoning Challenge (25-Shot)|47.95| |
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|HellaSwag (10-Shot) |74.62| |
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|MMLU (5-Shot) |40.39| |
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|TruthfulQA (0-shot) |38.91| |
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|Winogrande (5-shot) |72.06| |
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|GSM8k (5-shot) | 1.59| |
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