ctransformers
llama.cpp
ctransformers | llama.cpp | |
---|---|---|
4 | 780 | |
1,718 | 58,425 | |
- | - | |
8.6 | 10.0 | |
4 months ago | 2 days ago | |
C | C++ | |
MIT License | MIT License |
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ctransformers
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Refact LLM: New 1.6B code model reaches 32% HumanEval and is SOTA for the size
Does ctransformer (https://github.com/marella/ctransformers#supported-models) support running refact?
I see that model type "gpt_refact" in https://huggingface.co/smallcloudai/Refact-1_6B-fim/blob/mai...
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How do I utilize these quantized models being uploaded?
You can also use ctransformers with the ggml models if you want to use python rather than c++.
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Langchain and self hosted LLaMA hosted API
For ggml https://github.com/marella/ctransformers/ and https://github.com/abetlen/llama-cpp-python has a decent server. https://github.com/go-skynet/LocalAI is very active too.
- Also reconnecting with Scala. Interested in LLMs
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?
llama-cpp-python - Python bindings for llama.cpp
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
LangChain_PDFChat_Oobabooga - oobaboga -text-generation-webui implementation of wafflecomposite - langchain-ask-pdf-local
gpt4all - gpt4all: run open-source LLMs anywhere
text-generation-inference - Large Language Model Text Generation Inference
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
artificial-nose - Instructions, source code, and misc. resources needed for building a Tiny ML-powered artificial nose.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
kendryte-standalone-sdk - Standalone SDK for kendryte K210
ggml - Tensor library for machine learning
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM