torcheval
ClusterConfig
torcheval | ClusterConfig | |
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3 | 1 | |
196 | 12 | |
5.1% | - | |
7.5 | 5.8 | |
about 1 month ago | about 2 months ago | |
Python | Shell | |
GNU General Public License v3.0 or later | - |
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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 :)
ClusterConfig
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How Is LLaMa.cpp Possible?
I’ve been working through that repo and managed the 13B dataset on a single Pi4 8gig
I’ve also replicated the work in OpenMPI ( from a thread on the llama.cpp GitHub repo ) and today I managed to get the 65B dataset operational on three pi4 nodes.
I’m not saying this as any achievement of mine, but as a comment on the current reality of reproducible LLM At home on anything you’ve got.
It really feels like this technique has arrived.
https://github.com/cameronbunce/ClusterConfig
What are some alternatives?
tnt - A lightweight library for PyTorch training tools and utilities
llama2.cs - Inference Llama 2 in one file of pure C#
llama.cpp - LLM inference in C/C++
can-ai-code - Self-evaluating interview for AI coders
polyglot - Polyglot: Large Language Models of Well-balanced Competence in Multi-languages
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
ggllm.cpp - Falcon LLM ggml framework with CPU and GPU support
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