I do love that they've incorporated it onto facebook to make it easy to edit posts. According to the ChatBot him/herself/themselves, Llama is designed with safety in mind, which means this bot is less likely to provide harmful or offensive responses (compared to other popular ones like chatgpt). I am not sure how accurate that is, but it didn't provide me with any harmful or offensive responses. Review collected by and hosted on G2.com.

It doesn't have plugins or a voice assistant like chatgpt does. Review collected by and hosted on G2.com.

I use it every day to supplement OpenAI and Anthropic models as a low cost alternative for narrow use cases. easy accessibility and strong position as an open-source competitor. performance is great, particularly on optimized platforms like Groq delivering blazing speeds. multimodal AI offers versatile alternative to main providers, broadening the scope of AI applications Review collected by and hosted on G2.com.

very steerable but takes work, quite wordy by default, not fully reinforced, fine tuning is not easy, absence of the larger 400B mode restricts its ability to fully replace OpenAI or Anthropic models. lack of native infrastructure support through Meta means ease of setup is dependent on other platforms Review collected by and hosted on G2.com.

I like that this AI large language model provides easy to digest answers. I frequnently use it to compose or refine email blasts. I also use Llama 3 for day to day business tasks such as unit of measure conversions and to gain industry specific knowledge on various products and services. Meta's customer support is wonderful as well which makes resolving any issues a breeze, almost 0 down time. On top of that it's an easy tool to intergate into any business since it came be accessed from a web brower. Overall implementing and using Lamma 3 is really easy and a win win all around. Review collected by and hosted on G2.com.

Somtimes it's a little slow to respond but that's probably due to this being an emerging technology. Review collected by and hosted on G2.com.

Llama 3 blew me away with how well it understands what I'm saying and gives helpful answers. It feels almost like chatting with a real person! It's also super flexible and can be used for all sorts of stuff, from writing emails to helping with creative tasks. I've even seen people use it for complex stuff like financial modeling! Plus, it's open-source, so you can customize it to your heart's content. I use this model everyday to simplify my daily tasks. Review collected by and hosted on G2.com.

Honestly, the only thing that bugs me most about Llama 3 is that it needs a pretty beefy computer to run smoothly. Not everyone's got access to that kind of superpower. And sometimes it spits out answers that are just plain wrong or too simple. Still, gotta say, the good stuff outweighs the bad, but those are definitely some things they could improve on. Review collected by and hosted on G2.com.

The best thing about Meta Llama 3 is its open source accesibility,

without any barriers that are usually found in proprietary systems.

Its performance, its efficiently fine-tuned.

Thereby its pretty good at reasoning and code generation along with multi-step problem-solving tasks. Review collected by and hosted on G2.com.

On a personal note one thing that I dislike about Meta Llama 3 and especially the 70B model is that it demands very high computational power.

Being an open source this can be a barrier to individual developer who dont have access to high end infrastructure. Review collected by and hosted on G2.com.

We can easily finetune on custom dataset and the instruction following capability is the best. This version of Llama is much better than the Llama 2 which needed some careful prompt engineering to get specific output. Many open-source libraries support integration of Llama weights as promp-tuner for training vision LLMs which works the best for dense image captioning tasks. Review collected by and hosted on G2.com.

Currently the lightweight version are not available and the model is bulky and more inference turnaround time for small NLP tasks. Review collected by and hosted on G2.com.

There are many things that I like abour LLama 3:

Variable model sizes:The model sizes range from 8B to 70B parameters, which provides flexibility in computational power and application. This enables to control costs based on the use

Performance: The model is exceptional in performing day to day tasks and can be used for many enterprise solutions (complex RAG) and agentic frameworks. It beats most of the open source models in benchmarks

Community support & integration: Llama 3 has a very good community support. It has integrations in all the AI frameworks like llamaindex and langchain

Ease of use and: Its easy to self host it on gpu vms with good documentation. It is also supported by various frameworks like vllm, ollama etc Review collected by and hosted on G2.com.

Code generation: The code generated by Llama 3 are not so great. There are lot of errors and usually fails in generating non python codes

Loss of context: Even though the context length is huge, it tends to loose context after 5k tokens even in larger models

Potential for Misuse: The open-source nature of Meta Llama 3, while democratizing AI technology, also opens doors for misuse. I have already seen some people training it to generate misinformation and other malicious activities Review collected by and hosted on G2.com.

I appreciate MetaLlama3's overall capabilities and performance. It's a solid AI model that can handle a wide range of tasks reasonably well. The responses are often informative, logical, and well-written. I also like that the model tries to be engaging and entertaining in its communication style. Review collected by and hosted on G2.com.

While MetaLlama3 is generally satisfactory, there are a few areas where it could be improved compared to some other AI models. At times, the responses can lack depth or nuance, and the model may struggle with more complex or niche topics. Additionally, the conversational abilities could be smoother and more natural. There's room for enhancement in terms of contextual understanding and seamless back-and-forth dialogue.

Overall, MetaLlama3 is a capable AI assistant, but it doesn't quite reach the level of excellence that some competing models have achieved. With some refinements and advancements, it could become a top-tier option in the AI space. Review collected by and hosted on G2.com.

What I like best about Meta LLaMA 3 is its advanced contextual understanding, which enables it to generate highly accurate and relevant responses. This greatly enhances its versatility in applications like chatbots and content creation, making interactions more natural and effective. Review collected by and hosted on G2.com.

One thing I dislike about Meta LLaMA 3 is its potential resource intensity. Running such an advanced model can require significant computational power and memory, which might be a limitation for smaller organizations or individual users with limited access to high-end hardware. Additionally, despite its advanced capabilities, there can still be occasional inaccuracies or biases in the generated responses, which highlights the need for continuous refinement and monitoring. Review collected by and hosted on G2.com.

1. High-Quality Outputs: The language generation capabilities are top-notch, producing coherent and contextually appropriate responses across diverse applications.

2. Adaptability: Meta LLaMA 3 adapts well to different tasks, whether it’s for customer support, training, or creative content generation. Its ability to handle a wide range of topics makes it an excellent tool for our needs.

3. Customization: The model offers robust customization options, allowing us to fine-tune it for specific use cases. This has significantly enhanced the relevance and accuracy of the outputs.

4. Efficiency: The processing speed is impressive, enabling us to handle large volumes of queries and tasks without significant delays. Review collected by and hosted on G2.com.

1. Learning Curve: There is a bit of a learning curve in understanding and fully utilizing the customization features. However, once mastered, the benefits outweigh the initial effort.

2. Resource Intensive: Running such a powerful model requires substantial computational resources. Smaller teams or those with limited infrastructure may find it challenging to deploy.

3. Cost: While the performance is exceptional, the cost associated with licensing and maintaining Meta LLaMA 3 can be high, especially for startups or small businesses. Review collected by and hosted on G2.com.