You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
52 lines
1.5 KiB
52 lines
1.5 KiB
# ggml
|
|
|
|
Tensor library in C for machine learning
|
|
|
|
## Features
|
|
|
|
- Automatic differentiation (WIP)
|
|
- 16-bit float support
|
|
- ADAM and L-BFGS optimizers
|
|
- Optimized for Arm64 architectures (i.e. MacBook M1) via NEON intrinsics
|
|
- On x86 architectures utilzes AVX intrinsics
|
|
- No third-party dependencies
|
|
- Zero memory allocations during runtime
|
|
|
|
## Local GPT inference
|
|
|
|
Using ggml you can run [GPT-2](examples/gpt-2) and [GPT-J](examples/gpt-j) inference locally on your computer without any additional software or hardware. You don't even need to install python or any other third-party library.
|
|
|
|
The example programs are implemented in C++. They run entirely on the CPU.
|
|
|
|
Here is how to use them:
|
|
|
|
```bash
|
|
# Build ggml + examples
|
|
git clone https://github.com/ggerganov/ggml
|
|
cd ggml
|
|
mkdir build && cd build
|
|
cmake ..
|
|
make -j4 gpt-2 gpt-j
|
|
|
|
# Run the GPT-2 small 117M model
|
|
../examples/gpt-2/download-ggml-model.sh 117M
|
|
./bin/gpt-2 -m models/gpt-2-117M/ggml-model.bin -p "This is an example"
|
|
|
|
# Run the GPT-J 6B model (requires 12GB disk space and 16GB CPU RAM)
|
|
../examples/gpt-j/download-ggml-model.sh 6B
|
|
./bin/gpt-j -m models/gpt-j-6B/ggml-model.bin -p "This is an example"
|
|
```
|
|
|
|
This is the inference speed for the different models on my MacBook M1 Pro:
|
|
|
|
| Model | Size | Time / Token |
|
|
| --- | --- | --- |
|
|
| GPT-2 | 117M | 5 ms |
|
|
| GPT-2 | 345M | 12 ms |
|
|
| GPT-2 | 774M | 23 ms |
|
|
| GPT-2 | 1558M | 42 ms |
|
|
| --- | --- | --- |
|
|
| GPT-J | 6B | 125 ms |
|
|
|
|
For more information, checkout the corresponding programs in the [examples](examples) folder.
|