torcheval
tnt
| torcheval | tnt | |
|---|---|---|
| 3 | 1 | |
| 196 | 1,633 | |
| 5.1% | 0.6% | |
| 7.5 | 9.6 | |
| about 1 month ago | 4 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
torcheval
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How Is LLaMa.cpp Possible?
Reading this could make people believe it is computed from the probability distribution of the model alone.
To be clearer, it is the exponent of the average negative log probability that the model gives to the real tokens of a sample text[0]. Roughly, it relates to how strongly the model can predict the sample text. A perfect model would have zero perplexity; a random model has a perplexity equal to the number of possible tokens; the worst model has infinite perplexity.
[0]: https://github.com/pytorch/torcheval/blob/3faf19c060b8a7c074...
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What skills are necessary to understand/be able to make meaningful contributions to PyTorch?
Shameless plug, my team works on torcheval and torchtnt. Neither of them are core pytorch, but if you're looking to help build out tooling for metric evaluation or training frameworks, both libraries are pretty new with very low hanging fruit.
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[D] AMA: The Stability AI Team
Hey I work on TorchEval let us know if we can be of any help here :)
tnt
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What skills are necessary to understand/be able to make meaningful contributions to PyTorch?
Shameless plug, my team works on torcheval and torchtnt. Neither of them are core pytorch, but if you're looking to help build out tooling for metric evaluation or training frameworks, both libraries are pretty new with very low hanging fruit.
What are some alternatives?
llama.cpp - LLM inference in C/C++
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
polyglot - Polyglot: Large Language Models of Well-balanced Competence in Multi-languages
AgileRL - Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
ggllm.cpp - Falcon LLM ggml framework with CPU and GPU support
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion - A latent text-to-image diffusion model
llama2.cs - Inference Llama 2 in one file of pure C#
ClusterConfig - Guide to deploying Slurm and OpenMPI on Raspberry Pi computers
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI