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Best Platform for Working with Language Models
What do you like best about the product?
Hugging face have all the pre-trained models. They provide easy to use interface and all the support functions that can be required for working with models.
What do you dislike about the product?
There is nothing to dislike about hugging face. There libraby is perfect for using transformer models and for research as well.
What problems is the product solving and how is that benefiting you?
I have been working with language modeling and understanding how language model works. Creating chatbots using pre-trained models which hugging face make very easy for me.
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Jack of all trades for your AI needs with an extremely powerful community
What do you like best about the product?
Where do I even begin?
It's easily the best place for open source AI by a mile, may it be LLMs, diffusion models, audio models, APIs...you name it. You can create and upload your datasets, models, download them etc and the storage space on the free tier is very genorous. Huggingface spaces can be used to deploy your ML apps using powerful tools such as Gradio (another huggingface contribution), streamlit etc, the free tier gives a CPU and 16GB memory, and there's no limit on how many spaces you can create (at least, I think so).
Huggingface transformers has been a revolutionary gamechanger in AI development. Install it in python using pip, load the transformer by just the repository + model name and you're ready to go. How cool and easy is that?
The choice of ML models seems so be endless. For an example, we can freely download a 4GB-7GB sized Zephyr model that can beat ChatGPT while running on a CPU thanks to people like TheBloke who uploads quantised fine-tuned LLaMa2 models.
The biggest strength is of course, the community. Its such a fast growing platform thanks to hundreds of thousands of open source contributors and users. And there's a active discord community of 61000 members (as of now) where you can freely interact, learn, develop and contribute. Huggingface even offers you three free courses about NLP, Reinforcement Learning(with certification) and Audio AI, and they're adding more.
Ultimately, it wouldn't be an exaggeration to say the growth of AI and AI products wouldn't have happened this fast without Huggingface. Even their logo and website design has a refreshing effect on the mind
It's easily the best place for open source AI by a mile, may it be LLMs, diffusion models, audio models, APIs...you name it. You can create and upload your datasets, models, download them etc and the storage space on the free tier is very genorous. Huggingface spaces can be used to deploy your ML apps using powerful tools such as Gradio (another huggingface contribution), streamlit etc, the free tier gives a CPU and 16GB memory, and there's no limit on how many spaces you can create (at least, I think so).
Huggingface transformers has been a revolutionary gamechanger in AI development. Install it in python using pip, load the transformer by just the repository + model name and you're ready to go. How cool and easy is that?
The choice of ML models seems so be endless. For an example, we can freely download a 4GB-7GB sized Zephyr model that can beat ChatGPT while running on a CPU thanks to people like TheBloke who uploads quantised fine-tuned LLaMa2 models.
The biggest strength is of course, the community. Its such a fast growing platform thanks to hundreds of thousands of open source contributors and users. And there's a active discord community of 61000 members (as of now) where you can freely interact, learn, develop and contribute. Huggingface even offers you three free courses about NLP, Reinforcement Learning(with certification) and Audio AI, and they're adding more.
Ultimately, it wouldn't be an exaggeration to say the growth of AI and AI products wouldn't have happened this fast without Huggingface. Even their logo and website design has a refreshing effect on the mind
What do you dislike about the product?
Nothing at all, and I'm sure any possible weaknesses would already be covered by the community in some way
What problems is the product solving and how is that benefiting you?
I first came across Huggingface for trying to learn Reinforcement learning, it was a free and certified course at the highest level. I also learned the Natural Language Processing course after that. I've downloaded several models from various souces than I would care to count.
One particular case was when I was tasked with building a chatbot for an internship. I built it using an open source Zephyr-7B-beta model I downloaded from Huggingface, I also used huggingface transformers to integrate whisper AI so the chatbot can have voice-to-text functionality. And finally I deployed the bot using Huggingface spaces, so it can even be used as an API or integrate it into different platforms such as discord. And all thanks to Huggingface
One particular case was when I was tasked with building a chatbot for an internship. I built it using an open source Zephyr-7B-beta model I downloaded from Huggingface, I also used huggingface transformers to integrate whisper AI so the chatbot can have voice-to-text functionality. And finally I deployed the bot using Huggingface spaces, so it can even be used as an API or integrate it into different platforms such as discord. And all thanks to Huggingface
Hugging face review from AI engineer
What do you like best about the product?
Hugging Face is a platform for AI engineers that helps us to build, train deploy AI ML models. it gives pre-trained models that are pre-trained on very large data. We just need to use that infrastructure and train and deploy our own model. they have a Model Repository for Computer vision, NLP, and AI tasks. It is open- A source tool for any business with basic AI knowledge and uses the pre-trained model from hugging face and deploying model for their business. It has an AI community where you can share and view AI research best platform for Research and deployment. It saves much of AI engineer time cost cost-effective and needs less GPU to train as we can use pre-trained API.
What do you dislike about the product?
There is not much but sometimes Bias in NLP-trained models like LLm. Some of the file is too large to load. Some models are not that accurate or useful.
What problems is the product solving and how is that benefiting you?
NLP LLM chatbot, and in my computer vision project pre-trained models have helped me a lot.
"Transformative GenAI Natural Language Processing with Hugging Face: A Game-Changer!"
What do you like best about the product?
provides access to cutting-edge pre-trained language models like GPT-3.5 or other models
Open source community with wealth of coe samples, datasets & documentation. I used personally Bloom chat , dolly from databricks from here.
Highly scalable & can be useful for broad range of tasks like content summarization, language transation to chatbots
use of use & customization using fine-tuning/custom training
It support multi languages
Open source community with wealth of coe samples, datasets & documentation. I used personally Bloom chat , dolly from databricks from here.
Highly scalable & can be useful for broad range of tasks like content summarization, language transation to chatbots
use of use & customization using fine-tuning/custom training
It support multi languages
What do you dislike about the product?
Using powerful models, especially in high-demand scenarios, can incur substantial expenses.
Resource Intensiveness: Fine-tuning models and working with large language models like GPT-3.5 can be resource-intensive, requiring substantial computational power and storage.
Ethical concerns, Data Privacy,Model Size & sometime model availablity
Resource Intensiveness: Fine-tuning models and working with large language models like GPT-3.5 can be resource-intensive, requiring substantial computational power and storage.
Ethical concerns, Data Privacy,Model Size & sometime model availablity
What problems is the product solving and how is that benefiting you?
provides access to cutting-edge pre-trained language models like GPT-3.5 or other models
Open source community with wealth of coe samples, datasets & documentation. I used personally Bloom chat , dolly from databricks from here. - Variety of models
Highly scalable & can be useful for broad range of tasks like content summarization, language transation to chatbots - RAG Chat Bot with vector based search
use of use & customization using fine-tuning/custom training - Domain specific industry tuned model with enterpise data
It support multi languages - Language transalation from 1 language to another
Open source community with wealth of coe samples, datasets & documentation. I used personally Bloom chat , dolly from databricks from here. - Variety of models
Highly scalable & can be useful for broad range of tasks like content summarization, language transation to chatbots - RAG Chat Bot with vector based search
use of use & customization using fine-tuning/custom training - Domain specific industry tuned model with enterpise data
It support multi languages - Language transalation from 1 language to another
Review on Hugging Face
What do you like best about the product?
Hugging Face is way ahead with its extensive Model Hub.
Offers pre-trained models for NLP. and is also known for open-source contributions, APIs, and a great community.
It simplifies NLP tasks a lot.
Offers pre-trained models for NLP. and is also known for open-source contributions, APIs, and a great community.
It simplifies NLP tasks a lot.
What do you dislike about the product?
There are not any specific features or reasons to dislike that I can think of
What problems is the product solving and how is that benefiting you?
Because of the extensive Model Hub, it provides the option to choose from a wide range of pre-trained NLP models.
It is used mostly to simplify text generation and for checking the classification of certain business requirements.
It is used mostly to simplify text generation and for checking the classification of certain business requirements.
Great community!
What do you like best about the product?
Lots of great models, datasets and spaces to review
What do you dislike about the product?
A lot to learn for newbies. I'm still learning.
What problems is the product solving and how is that benefiting you?
Trying to learn more about machine learning
A great place to sample early-look AI tools
What do you like best about the product?
Hugging Face has a great collection of AI tools, and kicking the tires on the various apps can give you a real look at what AI can do.
What do you dislike about the product?
It can be a little challenging to navigate, but once you figure it out, the platform is very usable.
What problems is the product solving and how is that benefiting you?
Hugging Face lets me try out a smorgasbord of tools and work out what fits my workload.
Excellent one-stop-solution to all things AI/ML/DS
What do you like best about the product?
It is OPEN-SOURCE. Curated list of up-tp-date information on innovation around AI. Contains a large community of developers and artificial intelligence experts to aid any level (novice/amateur to pros) of personnel or firm to easily integrate state of the art AI techniques in their product offerings.
What do you dislike about the product?
The homepage is a little overwhelming and hard to navigate for a Data Scientist starting out in the industry but incremental refinements by the company and time resolves this minor hiccup.
What problems is the product solving and how is that benefiting you?
It is helping us easily integrate and deploy production ready open source large language models to help in our business applications
Easy to use APIs
What do you like best about the product?
I use their APIs for my NLP models which make it easier for me to implement my NLP solutions.
What do you dislike about the product?
One thing i noticed as they host wide range of pre-trained models, concerns about licensing do arise.
What problems is the product solving and how is that benefiting you?
I was able to get addressed knowledge gaps through their tutorials, educational materials and courses.
cutting- edge NLP models
What do you like best about the product?
They play significant role for my work by giving open source accessibility and large model repository.
What do you dislike about the product?
Only concern I found was resource -intensive in terms of memory and computation.
What problems is the product solving and how is that benefiting you?
I don't need to train my models from scratch as it has centralised pre- trained models
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