31–40 of 76 posts
Despite being only 1.1B params, SantaCoder outperforms Facebook's InCoder (6.7B params) and Salesforce's CodeGen-Multi-2.7B. Paper: https://hf.co/datasets/bigcode/admin/resolve/main/BigCode_Sa... Dataset search: https://huggingface.co/spaces/bigcode/santacoder-search Model weights: https://huggingface.co/bigcode/santacoder
Any idea how this, and those other two models, would compare to GitHub Copilot?
> e investigate the impact of 4 preprocessing methods on the training data: filtering files from repositories with 5+ GitHub stars, filtering files with a high comments-to- code ratio, more aggressive filtering of near-duplicates, and filtering files with a low character-to-token ratio. We observe modest impact of the new filters except for the stars filter, which deteriorates performance on text2code benchmarks significantly. This is an interesting result given that previous work has explicitly filtered for GitHub Stars as a proxy for data quality
Is anyone else here building AI programming services based on models like this? I see a lot of comments saying the models can't do much programming. But I just suspect there must be a silent contingent that is also working on services like that. And maybe less likely to promote the abilities of these models because it encourages competition.
IMO tough question of who can do codegen as a scalable standalone startup, but that's ok. Pretty darn easy & useful for many productivity platforms like ours where it's just a super nice feature as part of delivering a broader magical experience.
Related: we are hiring a k8s/pydata person, ideally who has need a user & builder of investigation platforms, as we are working w co's like Nvidia to bring this kind of thing to some pretty major enterprise & gov teams. See gdoc linked on our careers page.
Is anyone else here building AI programming services based on models like this? I see a lot of comments saying the models can't do much programming. But I just suspect there must be a silent contingent that is also working on services like that. And maybe less likely to promote the abilities of these models because it encourages competition.
Have there been examples of novel code, i.e. code that was not in the input set?
I think my job is safe. def all_odd_prime_elements(sequence): """Returns every odd prime element of the sequence.""" return [x for x in sequence if x % 2 == 1] def all_even_prime_elements(sequence): """Returns every even prime element of the sequence.""" return [x for x in
You can increase the number of tokens to be generated in "Advanced Settings"
Earlier quoted context omitted.
We use a few depending on the task (Codex, fine-tuned T5, Bert models, etc.). Constantly experimenting with different variations. Since we focus on solving narrower problems in more depth, it leaves more room for optimizing accuracy.
Have you been able to get your rate limit increased for code-davinci-002? It defaults to a very small amount.
- def closest_point_on_curve(target,curve):
"""Returns the 3D point on the curve closest to target 3D point"""
- return closest_point_on_curve_3d(target,curve)
Didn't work for me - def closest_point_on_curve(target,curve): """Returns the 3D point on the curve closest to target 3D point""" Response: - return closest_point_on_curve_3d(target,curve)