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examples : fix some typos in examples/model-conversion/README.md (#15477)
Signed-off-by: Jie Fu <jiefu@tencent.com>
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@ -6,7 +6,7 @@ The motivation for having this is that the conversion process can often be an
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iterative process, where the original model is inspected, converted, updates
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made to llama.cpp, converted again, etc. Once the model has been converted it
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needs to be verified against the original model, and then optionally quantified,
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and is some cases perplexity checked of the quantized model. And finally the
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and in some cases perplexity checked of the quantized model. And finally the
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model/models need to the ggml-org on Hugging Face. This tool/example tries to
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help with this process.
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@ -62,7 +62,7 @@ Command line arguments take precedence over environment variables when both are
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In cases where the transformer implementation for the model has not been released
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yet it is possible to set the environment variable `UNRELEASED_MODEL_NAME` which
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will the cause the transformer implementation to be loaded explicitely and not
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will then cause the transformer implementation to be loaded explicitely and not
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use AutoModelForCausalLM:
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```
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export UNRELEASED_MODEL_NAME=SomeNewModel
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@ -87,7 +87,7 @@ from the converted model.
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# Or using command line argument
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(venv) $ make causal-run-original-model MODEL_PATH=~/work/ai/models/some_model
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```
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This command will save two file to the `data` directory, one is a binary file
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This command will save two files to the `data` directory, one is a binary file
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containing logits which will be used for comparison with the converted model
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later, and the other is a text file which allows for manual visual inspection.
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@ -128,11 +128,11 @@ Quantized model saved to: /path/to/quantized/model-Q8_0.gguf
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Export the quantized model path to QUANTIZED_MODEL variable in your environment
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```
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This will show the path to the quantized model in the terminal, which can then
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be used set the `QUANTIZED_MODEL` environment variable:
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be used to set the `QUANTIZED_MODEL` environment variable:
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```console
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export QUANTIZED_MODEL=/path/to/quantized/model-Q8_0.gguf
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```
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The the quantized model can be run using the following command:
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Then the quantized model can be run using the following command:
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```console
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(venv) $ make causal-run-quantized-model
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```
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@ -229,11 +229,11 @@ Quantized model saved to: /path/to/quantized/model-Q8_0.gguf
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Export the quantized model path to QUANTIZED_EMBEDDING_MODEL variable in your environment
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```
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This will show the path to the quantized model in the terminal, which can then
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be used set the `QUANTIZED_EMBEDDING_MODEL` environment variable:
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be used to set the `QUANTIZED_EMBEDDING_MODEL` environment variable:
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```console
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export QUANTIZED_EMBEDDING_MODEL=/path/to/quantized/model-Q8_0.gguf
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```
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The the quantized model can be run using the following command:
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Then the quantized model can be run using the following command:
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```console
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(venv) $ make embedding-run-quantized-model
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```
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@ -246,7 +246,7 @@ token/logits file:
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```console
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(venv) $ make perplexity-run QUANTIZED_MODEL=~/path/to/quantized/model.gguf
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```
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This will use the wikitext dataset to run the perplexity evaluation and and
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This will use the wikitext dataset to run the perplexity evaluation and
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output the perplexity score to the terminal. This value can then be compared
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with the perplexity score of the unquantized model.
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