Our struggle with Word and LaTeX in formatting journal submissions and academic assignments led us to build Typeset. We realised that no one had designed a platform that was dedicated to meet the needs of people like you, who generate billions of pieces of academic work each year. We found that Word and Google Docs are unstructured and need constant re-editing and re-formatting, while LaTeX is too hard for most researchers. Typeset intends to be the perfect bridge - ease of intuitive writing and collaboration, with the rigor and power of LaT
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Based on our record, Hugging Face should be more popular than Typeset. 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.
Try SciSpace to search for journal articles. It uses AI to summarize all the key components of the research papers that come up in your search query. Just don't copy/paste the summaries into your assignment because they'll get flagged as AI content. Source: 5 months ago
If you're currently subscribed to ChatGPT Plus, then you can also use ResearchGPT for free: https://chat.openai.com/g/g-bo0FiWLY7-researchgpt. It is a collaboration between SciSpace (typeset.io) and OpenAI. Promised to give accurate citations and information (I only use the free SciSpace version so I'm not sure how great their new product is). Source: 5 months ago
- https://typeset.io/ Do any of you have any experience with these tools? Jenni ai seems interesting, I guess. - Source: Hacker News / 9 months ago
Discover, Create, and Publish your research paper | SciSpace by Typeset ( https://typeset.io/ ). Source: 11 months ago
Two other tools I didn't have a chance to try for academic research papers is scholarcy.com and https://typeset.io/ (called SciSpace). Source: 12 months ago
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 / 22 days ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / 28 days 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
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