bigscience
blackjack-discard-tray-photos
| bigscience | blackjack-discard-tray-photos | |
|---|---|---|
| 4 | 1 | |
| 939 | 2 | |
| 0.7% | - | |
| 3.2 | 0.0 | |
| 6 months ago | almost 2 years ago | |
| Shell | Shell | |
| GNU General Public License v3.0 or later | MIT License |
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bigscience
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[N] Live and open training of BigScience's 176B multilingual language model has just started
Details on the distributed setup used for the training: https://github.com/bigscience-workshop/bigscience/tree/master/train/tr11-176B-ml
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[Announcement] HuggingFace BigScience AMA Thursday, March 24th from 5pm CET
Model architecture and a blog post on decisions on architecture, size, shape, and pretraining duration
- Where can I see what languages the dataset consists of, which recently started training an open-source model 176B parameters by BigScience Workshop?
- Lessons learned from training 104B model
blackjack-discard-tray-photos
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365 sequential photos of cards in a discard tray
I wanted to practice deck estimation so I took a bunch of photos of cards in a discard tray. The plan was to build a web app that shows one photo and tests the user on how many cards are in the tray. I haven't had time to build it yet but I figured I'd share the photos in case anyone has a use for them: https://github.com/mhluska/blackjack-discard-tray-photos/releases/download/v0.0.1/discard-tray-photos-v0.0.1.zip
What are some alternatives?
lm-evaluation-harness - A framework for few-shot evaluation of language models.
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security-training - Public version of PagerDuty's employee security training courses.
cka-crash-course - In-depth and hands-on practice for acing the exam.
container.training - Slides and code samples for training, tutorials, and workshops about Docker, containers, and Kubernetes.
spacy-models - 💫 Models for the spaCy Natural Language Processing (NLP) library
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
t-zero - Reproduce results and replicate training fo T0 (Multitask Prompted Training Enables Zero-Shot Task Generalization)