KissanAI introduces Dhenu Llama 3, an AI model tailored for agriculture, based on Llama3 8B architecture

  • KissanAI introduces Dhenu Llama 3, an advanced AI model for agriculture, fine-tuned on Llama3 8B architecture.
  • Meta unveils Llama 3, available in 8B and 70B parameter versions, trained on a vast dataset exceeding 15 trillion tokens.
  • Dhenu Llama 3 offers enhanced reasoning and coding capabilities, with a training process three times more efficient than its predecessor.
  • Models are accessible on Hugging Face, with a stipulated naming convention for derivative AI models.
  • Meta develops a massive model with over 400 billion parameters, aiming for industry-leading performance.
  • Llama 3 models outperform competitors on benchmarks, rolling out across major platforms and hardware providers.
  • KissanAI’s Dhenu 1.0, released previously, supports Indian farmers with multilingual capabilities and extensive datasets.

Main AI News:

In a groundbreaking move for the agricultural sector, KissanAI has proudly introduced Dhenu Llama 3, a sophisticated AI model finely honed on the advanced Llama3 8B architecture. This momentous release was heralded by none other than KissanAI’s visionary founder, Pratik Desai.

Desai expressed, “It is open for exploration and feedback from all enthusiasts. Should you possess a spare GPU, we encourage you to experiment and share your insights. In the near future, an instructional version boasting a dataset five times larger will be made available.

Recently, Meta made waves with the unveiling of Llama 3. This cutting-edge model is offered in both 8B and 70B parameter variants and has undergone training on a staggering corpus of over 15 trillion tokens, rendering it seven times more expansive than its predecessor, Llama 2. Noteworthy advancements include augmented reasoning capabilities and coding proficiencies, coupled with a training regimen that boasts threefold efficiency gains over its forerunner.

Excitingly, these models have now found a new home on Hugging Face, further expanding their accessibility and utility.

Of particular interest is the stipulation within the Community License Agreement set forth by the company. It mandates that any AI model developed, refined, or distributed using Llama Materials must bear the prefix “Llama 3” in its nomenclature, a testament to the enduring legacy of this groundbreaking technology.

Meta continues to push the boundaries with its ambitious endeavors, including the ongoing development of a colossal model boasting over 400 billion parameters. As Mark Zuckerberg himself proclaimed in a Reel on Instagram, this upcoming model is poised to redefine performance benchmarks across the industry.

The efficacy of Llama 3 models is evident in their superior performance across a spectrum of benchmarks. The 7B iteration surpasses Gemma and Mistral, while the formidable 70B variant outshines Gemini Pro 1.5 and Claude 3 Sonnet, solidifying their position as the pinnacle of AI innovation.

Excitingly, these cutting-edge models are now being seamlessly integrated into prominent platforms such as Amazon SageMaker, Databricks, Google Cloud, Hugging Face, Kaggle, IBM WatsonX, Microsoft Azure, NVIDIA NIM, and Snowflake. Furthermore, compatibility with hardware solutions from AMD, AWS, Dell, Intel, NVIDIA, and Qualcomm ensures widespread accessibility and adoption.

Building upon the success of Dhenu 1.0, released last year, KissanAI continues to champion the cause of Indian agriculture with its latest offering. Dhenu 1.0, constructed on the robust Llama 2 framework, caters to the linguistic preferences of farmers by comprehending English, Hindi, and Hinglish. Armed with extensive datasets and capable of processing 300,000 instructions in both languages, Dhenu 1.0 stands as a beacon of support for farmers seeking actionable insights and guidance.


The introduction of Dhenu Llama 3 marks a significant leap forward in agricultural AI solutions, promising enhanced capabilities and performance benchmarks that position it as a leader in the market. With widespread accessibility and compatibility across major platforms and hardware providers, its impact on the agricultural sector is poised to be profound, empowering farmers with actionable insights and support.