Search Results for author:
Found 6 papers, 0 papers with code
PARAMANU-GANITA: Language Model with Mathematical Capabilities
In the end, we want to point out that we have only trained Paramanu-Ganita only on a part of our entire mathematical corpus and yet to explore the full potential of our model.
PARAMANU-AYN: An Efficient Novel Generative and Instruction-tuned Language Model for Indian Legal Case Documents
We also evaluated the responses of prompts for instruction-tuned models by GPT-3. 5-Turbo on clarity, relevance, completeness, and legal reasoning metrics in a scale of 10.
Neural Models for Source Code Synthesis and Completion
In this master thesis, we present sequence-to-sequence deep learning models and training paradigms to map NL to general-purpose programming languages that can assist users with suggestions of source code snippets, given a NL intent, and also extend auto-completion functionality of the source code to users while they are writing source code.
Paramanu: A Family of Novel Efficient Indic Generative Foundation Language Models
It is a collection of auto-regressive monolingual, bilingual, and multilingual Indic language models pretrained from scratch on a single GPU for 10 Indian languages (Assamese, Bangla, Hindi, Konkani, Maithili, Marathi, Odia, Sanskrit, Tamil, Telugu) across 5 scripts (Bangla, Devanagari, Odia, Tamil, Telugu) of varying sizes ranging from 13. 29M to 367. 5M. The models are pretrained with a context size of 1024 on a single GPU.
Learning Multilingual Embeddings for Cross-Lingual Information Retrieval in the Presence of Topically Aligned Corpora
The proposed method is superior to the state-of-the-art method not only for IR evaluation measures but also in terms of time requirements.
Discovering conversational topics and emotions associated with Demonetization tweets in India
As one showcase, in this paper, we summarize the data set of Twitter messages related to recent demonetization of all Rs.
