Open-Llama
llama.cpp
Open-Llama | llama.cpp | |
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7 | 778 | |
637 | 57,984 | |
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10.0 | 10.0 | |
about 1 year ago | 3 days ago | |
Python | C++ | |
MIT License | MIT License |
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Open-Llama
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(1/2) May 2023
Training code of the open-source high-performance Llama model, including the full process from pre-training to RLHF (https://github.com/s-JoL/Open-Llama)
- Open-Lamam: A “real” open-source project to train LLM not just checkpoints
- Open-Lamam: A real open-source project to train LLM
- Open-Llama: A Open Source Project for Training Language Models
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OpenLLaMA: An Open Reproduction of LLaMA
Really exciting how fast fully pre-trained new models are appearing.
Here's another repo (with the same "open-llama" name) that has been available on hugging face as well for a few weeks. (different training dataset)
https://github.com/s-JoL/Open-Llama
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Build your onw LLM 101
Open-Llama
- Open-Llama is an open source project that provides a complete set of training processes for building large-scale language models, from data preparation to tokenization, pre-training, instruction tuning, and reinforcement learning techniques such as RLHF.
llama.cpp
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IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
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Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
What are some alternatives?
open_llama - OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
gpt4all - gpt4all: run open-source LLMs anywhere
My-Medium-Articles-Friendly-Links - Friendly link to all of my medium articles
AgileRL - Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
ggml - Tensor library for machine learning
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.
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM