初始化项目，由ModelHub XC社区提供模型

Model: QuantFactory/sarvam-2b-v0.5-GGUF
Source: Original Platform

README.md

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+
+---
+
+library_name: transformers
+license: other
+
+---
+
+![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)
+
+# QuantFactory/sarvam-2b-v0.5-GGUF
+This is quantized version of [sarvamai/sarvam-2b-v0.5](https://huggingface.co/sarvamai/sarvam-2b-v0.5) created using llama.cpp
+
+# Original Model Card
+
+
+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!
+
+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.
+
+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.
+
+Getting started:
+```
+from transformers import pipeline
+pipe = pipeline(model='sarvamai/sarvam-2b-v0.5', device=0)
+pipe('भारत के प्रथम प्रधानमंत्री', max_new_tokens=15, temperature=0.1, repetition_penalty=1.2)[0]['generated_text']
+# 'भारत के प्रथम प्रधानमंत्री जवाहरलाल नेहरू की बेटी इंदिरा गांधी थीं।\n\n'
+```
+
+More technical details like evaluations and benchmarking will be posted soon.