Promptify
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research (by promptslab)
finetuner
:dart: Task-oriented embedding tuning for BERT, CLIP, etc. (by jina-ai)
Our great sponsors
Promptify | finetuner | |
---|---|---|
29 | 36 | |
3,013 | 1,423 | |
3.6% | 1.7% | |
8.5 | 5.5 | |
about 1 month ago | about 1 month ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Promptify
Posts with mentions or reviews of Promptify.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-13.
-
Promptify 2.0: More Structured, More Powerful LLMs with Prompt-Optimization, Prompt-Engineering, and Structured Json Parsing with GPT-n Models! 🚀
First up, a huge Thank You for making Promptify a hit with over 2.3k+ stars on Github ! 🌟
-
A minimal design pattern for LLM-powered microservices with FastAPI & LangChain
You're absolutely correct, and I agree that there's potentially a risk of quality loss. But likewise, since these are all intrinsically linked, it may be possible to leverage strength by combining these tasks. I'm unaware of a paper reviewing the reliability and/or performance of LLMs in this specific scenario. If you find any, do share :) With regards to generating JSON responses - there are simple ways to nudge the model and even validate it, using libraries such as https://github.com/promptslab/Promptify, https://github.com/eyurtsev/kor and https://github.com/ShreyaR/guardrails
- Promptify: Prompt Engineering Library
-
A python module to generate optimized prompts, Prompt-engineering & solve different NLP problems using GPT-n (GPT-3, ChatGPT) based models and return structured python object for easy parsing
Examples: https://github.com/promptslab/Promptify/tree/main/examples
-
Promptify - Prompt Engineering for Named Entity Recognition(NER)
In this blog, we are going to try to understand how promptify is going to be used along with LLMs(Large Language Models) to perform named entity recognition(NER).
-
[D] What ML dev tools do you wish you'd discovered earlier?
Check Promptify for LLM https://github.com/promptslab/Promptify
-
[P] Extracting Causal Chains from Text Using Language Models
Awesome project! I am working on something similar using Promptify (extending this PR -> https://github.com/promptslab/Promptify/issues/3)
- Classification using prompt or fine tuning?
finetuner
Posts with mentions or reviews of finetuner.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-17.
-
How do you think search will change with technology like ChatGPT, Bing’s new AI search engine and the upcoming Google Bard?
And all of that has something to do with finetuners. It basically fine-tunes AI models for specific use cases. With it can create a custom search experience that is tailored to their specific needs. I also wonder how this is going to be integrated into SEO tools soon since those tools are catered to traditional search engines.
-
Combining multiple lists into one, meaningfully
Combining multiple lists into one is tough, but it's doable if you have the right approach. Fine-tuning GPT-3 might help, but finding enough examples is tough. You could use existing text data or manually label a set of training examples. A finetuner could be help too. It's a platform-agnostic toolkit that can fine-tune pre-trained models and it's customizable to do lots of tasks.
-
speech_recognition not able to convert the full live audio to text. Please help me to fine-tune it.
You can adjust the pause threshold a little longer for pauses between and phrases. You can also use the phrase detection mode, which sets a time limit for the entire phrase instead of ending the transcription prematurely. If your microphone sensitivity is low, you can also try adjusting the energy threshold. If you want, you can use finetuners.
-
Questions about fine-tuned results. Should the completion results be identical to fine-tune examples?
It's possible that completion results may be identical to fine-tuned examples, but not guaranteed. Even with the same prompt, slight variations in output are expected due to the nature of probabilistic language models. You can experiment with different settings and parameters, including those with finetuners like these.
-
How can I create a dataset to refine Whisper AI from old videos with subtitles?
You can try creating your own dataset. Get some audio data that you want, preprocess it, and then create a custom dataset you can use to fine tune. You could use finetuners like these if you want as well.
-
A Guide to Using OpenTelemetry in Jina for Monitoring and Tracing Applications
We derived the dataset by pre-processing the deepfashion dataset using Finetuner. The image label generated by Finetuner is extracted and formatted to produce the text attribute of each product.
-
[D] Looking for an open source Downloadable model to run on my local device.
You can either use Hugging Face Transformers as they have a lot of pre-trained models that you can customize. Or Finetuners like this one: which is a toolkit for fine-tuning multiple models.
-
Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models
Very recently, a few non-English and multilingual CLIP models have appeared, using various sources of training data. In this article, we’ll evaluate a multilingual CLIP model’s performance in a language other than English, and show how you can improve it even further using Jina AI’s Finetuner.
-
Is there a way I can feed the gpt3 model database object like tables? I know we can create fine tune model but not sure about the completion part. Please help!
I think you can convert your data into text and fine-tune the model on it. But that might not be the ideal way to go since you kind of base that on the model. Try transfer learning or finetuning with a finetuner.
-
Classification using prompt or fine tuning?
you can try prompt-based classification or fine-tuning with a Finetuner. Prompts work well for simple tasks but fine-tuning may give better results for complex ones. Althouigh it's going to need more resources, but try both and see what works best for you.
What are some alternatives?
When comparing Promptify and finetuner you can also consider the following projects:
causal-chains - Library for creating causal chains using language models.
gpt_index - LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]