quantized

candle-quantized-llama: Fast Inference of quantized LLaMA models

This example provides a quantized LLaMA model similar to llama.cpp. This is based on candle built-in quantization methods. Supported features include:

• 2-bit, 3-bit, 4-bit, 5-bit, 6-bit and 8-bit integer quantization support.
• SIMD optimizations on Apple Silicon and x86.
• Support using the gguf and ggml file formats.

The weights are automatically downloaded for you from the HuggingFace Hub on the first run. There are various command line flags to use local files instead, run with --help to learn about them.

Running some example.

cargo run --example quantized --release -- --prompt "The best thing about coding in rust is "

> avx: true, neon: false, simd128: false, f16c: true
> temp: 0.80 repeat-penalty: 1.10 repeat-last-n: 64
> loaded 291 tensors (3.79GB) in 2.17s
> params: HParams { n_vocab: 32000, n_embd: 4096, n_mult: 256, n_head: 32, n_layer: 32, n_rot: 128, ftype: 2 }
> The best thing about coding in rust is 1.) that I don’t need to worry about memory leaks, 2.) speed and 3.) my program will compile even on old machines.

Command-line flags

Run with --help to see all options.

• --which: specify the model to use, e.g. 7b, 13-chat, 7b-code.
• --prompt interactive: interactive mode where multiple prompts can be entered.
• --model mymodelfile.gguf: use a local model file rather than getting one from the hub.