45 lines
1.7 KiB
Markdown
45 lines
1.7 KiB
Markdown
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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.
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