Add a small readme for the quantized example. (#823)

candle-examples/examples/quantized/README.md

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+# candle-quantized-llama: Fast Inference of quantized LLaMA models
+
+This example provides a quantized LLaMA model similar to
+[llama.cpp](https://github.com/ggerganov/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](https://huggingface.co/) 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.
+
+```bash
+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.