blog
llama
| blog | llama | |
|---|---|---|
| 5 | 2 | |
| 2,025 | 80 | |
| 5.7% | - | |
| 9.8 | 6.2 | |
| 2 days ago | 10 months ago | |
| Jupyter Notebook | Python | |
| - | 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.
blog
-
Refact LLM: New 1.6B code model reaches 32% HumanEval and is SOTA for the size
[4] https://github.com/huggingface/blog/blob/main/starcoder.md
-
A comprehensive guide to running Llama 2 locally
If you just want to do inference/mess around with the model and have a 16GB GPU, then this[0] is enough to paste into a notebook. You need to have access to the HF models though.
0. https://github.com/huggingface/blog/blob/main/llama2.md#usin...
-
Let’s train your first Offline Decision Transformer model from scratch 🤖
The hands-on 👉https://github.com/huggingface/blog/blob/main/notebooks/101_train-decision-transformers.ipynb
-
How to switch to half precision fp16?
I'm also running the optimized script but it doesn't run with 512x512 on my RTX3050 Ti mobile. On this website, they recommend to switch to fp16 for GPUs with less than 10gb of vram.
-
Are people hiding their deep learning code?
Here's a notebook illustrating how to train a language model from scratch: https://github.com/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb
llama
-
A comprehensive guide to running Llama 2 locally
Self-plug. Here’s a fork of the original llama 2 code adapted to run on the CPU or MPS (M1/M2 GPU) if available:
https://github.com/krychu/llama
It runs with the original weights, and gets you to ~4 tokens/sec on MacBook Pro M1 with the 7B model.
-
Llama 2 – Meta AI
Version that runs on the CPU: https://github.com/krychu/llama
I get 1 word per ~1.5 secs on a Mac Book Pro M1.
What are some alternatives?
text-generation-inference - Large Language Model Text Generation Inference
llama2-chatbot - LLaMA v2 Chatbot
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
marsha - Marsha is a functional, higher-level, English-based programming language that gets compiled into tested Python software by an LLM
awesome-notebooks - A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.
OpenPipe - Turn expensive prompts into cheap fine-tuned models
QuantumKatas - Tutorials and programming exercises for learning Q# and quantum computing
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
cog - Containers for machine learning
Practical_RL - A course in reinforcement learning in the wild
llama.cppav