Also checkout https://text-generator.io its a multi modal model so visits any input links, downloads web pages and images are analyzed with NNs to make better text.

Also does speech to text/text to speech so can talk

As many have said lots of these things will likely/hopefully come together into something big, needs a few things like the when to train new tools/model zoo thing, but internally Text Generator is based on multiple models too and has some internal decision making for which model is best on every request (so you dont need to pick a code/text model it does it automatically) which is similar but it's not training new nets.

I recommend getting a box with a 3090 ti or upwards, it's much faster than a laptop GPU, on a 24g vram machine I can train a 3b model or do inference on a 11b one so training is much more intensive on the memory, also recommend looking into TRC where they will give you free tpu for a month, but still won't end up being completely free, also CloudFlare r3 sounds good for storing models but it's not really the storage/transfer costs that are important during experimental stuff anyway.

Thanks, also checkout https://text-generator.io as it's really efficient to try the pretrained models first instead of trying complex training

This is some truly epic prompting, checkout https://text-generator.io for replacing some of the gpt-instruct-13B queries to save cost, you can generate many results in a single inference too and are only charged for a whole request, then can rerank them.

Theres a lot of tricks in here like using a relevant/coherent detection network to rerank and using DPR to select relevant parts of the summary for the context. (see the utils in

```

dpr_query_encoder = SentenceTransformer('sentence-transformers/facebook-dpr-question_encoder-single-nq-base')

dpr_context_encoder = SentenceTransformer('sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base'))

```

a whole bunch of other models are loaded in there like for NER, entailment, QA using unifiedqa-t5-large, i find it a good reference for some good/appropriate to use models https://github.com/yangkevin2/emnlp22-re3-story-generation/blob/20a99853ff4acbdb11865f57f4fa74431af0b628/story_generation/common/util.py#L69

Bloom/gpt neo/codegen is a good one and all come in various sizes, CPUs are slow though vs GPUs even old GPUs.

Also try https://text-generator.io which is a much more cost effective way to prototype new tools/what's possible right now, way cheaper than OpenAi, does text and code and a 100 requests a month free teir, then you can drop down to doing it yourself once your at a large scale.

Text generator runs under a second normally on fast GPUs