32 lines
1.7 KiB
Markdown
32 lines
1.7 KiB
Markdown
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---
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library_name: transformers
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license: other
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---
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# QuantFactory/sarvam-2b-v0.5-GGUF
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This is quantized version of [sarvamai/sarvam-2b-v0.5](https://huggingface.co/sarvamai/sarvam-2b-v0.5) created using llama.cpp
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# Original Model Card
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Update (Aug 15, 2024): You can now get started with text completions and supervised finetuning using [this notebook](https://colab.research.google.com/drive/1IZ-KJgzRAMr4Rm_-OWvWwnfTQwRxOknp?usp=sharing) on Google colab!
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This is an early checkpoint of sarvam-2b, a small, yet powerful language model pre-trained from scratch on 4 trillion tokens. It is trained to be good at 10 Indic languages + English. Officially, the Indic languages supported are: Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, and Telugu.
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sarvam-2b will be trained on a data mixture containing equal parts English (2T) and Indic (2T) tokens. The current checkpoint has seen a total of 2 trillion tokens, and has not undergone any post-training.
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Getting started:
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```
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from transformers import pipeline
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pipe = pipeline(model='sarvamai/sarvam-2b-v0.5', device=0)
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pipe('भारत के प्रथम प्रधानमंत्री', max_new_tokens=15, temperature=0.1, repetition_penalty=1.2)[0]['generated_text']
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# 'भारत के प्रथम प्रधानमंत्री जवाहरलाल नेहरू की बेटी इंदिरा गांधी थीं।\n\n'
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```
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More technical details like evaluations and benchmarking will be posted soon.
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