FirstLanguage India
Wit.ai
Dialogflow
Replika
Mitsuku
Cleverbot.io
rasa NLU
Domain-Monitor.io
Hugging Face
Replika
LangChain
Haystack NLP Framework
Mitsuku
Cleverbot.io
Kuki
Civitai
Our motto is 'NLP for the masses'. As you all know NLP requires specialized developers to build language based apps. We usually talk about training models and picking the right algorithm for an NLP task like for example Sentiment Analysis. This may be daunting for non-NLP developers if they are not well versed with the subject.
Any developer with an idea related to any app which requires text or speech processing should be able to develop that idea into reality. We at FirstLanguage enable that by providing an easy to use API at an affordable cost for a wide range of NLP tasks.
We cater to basic building block tasks like Stemming, Lemmatizer, Morphological Analyzer, POStag etc to advanced tasks like Sentiment Analysis or classification, Question Answering, Translation, Summarization etc.
We provide a Free plan to try our API or build your prototype, no credit card required. It is free for life until you decide to upgrade.
We provide API documentation which explains each and every API and what it does and how to use it. The documentation page also provides Try It feature which you can use to try our APIs directly in the browser. The documentation also provides code snippets in multiple coding languages.
We also provide SDKs for our API in Python and Typescript.
FirstLanguage India Hugging FaceNo Hugging Face videos yet. You could help us improve this page by suggesting one.
Based on our record, Hugging Face seems to be more popular. It has been mentiond 252 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
HuggingFaceEmbeddings is a function that we use for converting our documents to vector which is called embedding, you can use any embedding model from huggingface, it will load the model on your local computer and create embeddings(you can use external api/service to create embeddings), then we just pass this to context and create index and store them into folder so we can reuse them and don't need to recalculate it. - Source: dev.to / 27 days ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / about 1 month ago
Finally, you'll need to download a compatible language model and copy it to the ~/llama.cpp/models directory. Head over to Hugging Face and search for a GGUF-formatted model that fits within your device's available RAM. I'd recommend starting with TinyLlama-1.1B. - Source: dev.to / about 1 month ago
At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / about 1 month ago
New models can be added by downloading GGUF format models to the models sub-directory from https://huggingface.co/. - Source: dev.to / about 2 months ago
Wit.ai - Easily create text or voice based bots that humans can chat with on their preferred messaging...
Replika - Your Ai friend
Dialogflow - Conversational UX Platform. (ex API.ai)
LangChain - Framework for building applications with LLMs through composability
Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.
Mitsuku - Browser-based, AI chat bot.