The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Sparsegpt Alternatives
Similar projects and alternatives to sparsegpt
-
text-generation-webui
A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
-
-
-
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
-
serge
A web interface for chatting with Alpaca through llama.cpp. Fully dockerized, with an easy to use API.
-
-
-
-
intel-extension-for-pytorch
A Python package for extending the official PyTorch that can easily obtain performance on Intel platform
-
promptfoo
Test your prompts, models, and RAGs. Catch regressions and improve prompt quality. LLM evals for OpenAI, Azure, Anthropic, Gemini, Mistral, Llama, Bedrock, Ollama, and other local & private models with CI/CD integration.
-
-
geov
The GeoV model is a large langauge model designed by Georges Harik and uses Rotary Positional Embeddings with Relative distances (RoPER). We have shared a pre-trained 9B parameter model.
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better sparsegpt alternative or higher similarity.
sparsegpt reviews and mentions
Posts with mentions or reviews of sparsegpt.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-02.
-
(1/2) May 2023
SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot (https://arxiv.org/abs/2301.00774)
- Why Falcon going Apache 2.0 is a BIG deal for all of us.
-
New Open-source LLMs! 🤯 The Falcon has landed! 7B and 40B
There is this : https://github.com/IST-DASLab/sparsegpt
-
Webinar: Running LLMs performantly on CPUs Utilizing Pruning and Quantization
Check the paper here, it's intersting: https://arxiv.org/abs/2301.00774
-
OpenAI chief goes before US Congress to propose licenses for building AI
There's no chance that we've peeked from a bang for buck sense - we still haven't adequately investigated sparse networks.
Relevantish: https://arxiv.org/abs/2301.00774
The fact that we can reach those levels of sparseness with pruning also indicates that we're not doing a very good job of generating the initial network conditions.
Being able to come up with trainable initial settings for sparse networks across different topologies is hard, but given that we've had a degree of success with pre-trained networks, pre-training and pre-pruning might also allow for sparse networks with minimally compromised learning capabilities.
If it's possible to pre-train composable network modules, it might also be feasible to define trainable sparse networks with significantly relaxed topological constraints.
-
How to run Llama 13B with a 6GB graphics card
Training uses gradient descent, so you want to have good precision during that process. But once you have the overall structure of the network, https://arxiv.org/abs/2210.17323 (GPTQ) showed that you can cut down the precision quite a bit without losing a lot of accuracy. It seems you can cut down further for larger models. For the 13B Llama-based ones, going below 5 bit per parameter is noticeably worse, but for 30B models you can do 4 bits.
The same group did another paper https://arxiv.org/abs/2301.00774 which shows that in addition to reducing the precision of each parameter, you can also prune out a bunch of parameters entirely. It's harder to apply this optimization because models are usually loaded into RAM densely, but I hope someone figures out how to do it for popular models.
- SparseGPT: Language Models Can Be Accurately Pruned in One-Shot
-
A note from our sponsor - WorkOS
workos.com | 28 Apr 2024
Stats
Basic sparsegpt repo stats
16
624
2.4
22 days ago
IST-DASLab/sparsegpt is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of sparsegpt is Python.
Popular Comparisons
Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com