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--- |
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license: mit |
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language: |
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- en |
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- kn |
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metrics: |
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- accuracy |
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pipeline_tag: text-generation |
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tags: |
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- bilingual |
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- kannada |
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- english |
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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. |
