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Update README and comments for standalone perplexity tool (#525)

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README.md
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@ -248,7 +248,7 @@ cadaver, cauliflower, cabbage (vegetable), catalpa (tree) and Cailleach.
### Perplexity (Measuring model quality)
You can pass `--perplexity` as a command line option to measure perplexity over the given prompt. For more background,
You can use the `perplexity` example to measure perplexity over the given prompt. For more background,
see https://huggingface.co/docs/transformers/perplexity. However, in general, lower perplexity is better for LLMs.
#### Latest measurements
@ -271,10 +271,10 @@ Perplexity - model options
#### How to run
1. Download/extract: https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip?ref=salesforce-research
2. Run `./main --perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
2. Run `./perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
3. Output:
```
Calculating perplexity over 655 chunks
perplexity : calculating perplexity over 655 chunks
24.43 seconds per pass - ETA 4.45 hours
[1]4.5970,[2]5.1807,[3]6.0382,...
```

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examples/perplexity/perplexity.cpp
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@ -19,7 +19,7 @@ std::vector<double> softmax(const std::vector<float>& logits) {
void perplexity(llama_context * ctx, const gpt_params & params) {
// Download: https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip?ref=salesforce-research
// Run `./main --perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
// Run `./perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
// Output: `perplexity: 13.5106 [114/114]`
auto tokens = ::llama_tokenize(ctx, params.prompt, true);