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5d6688de08
This commit updates the modelcard.template file used in the model conversion scripts for embedding models to include the llama-server --embeddings flag in the recommended command to run the model. The motivation for this change was that when using the model-conversion "tool" to upload the EmbeddingGemma models to Hugging Face this flag was missing and the embedding endpoint was there for not available when copy&pasting the command.
49 lines
1.3 KiB
Plaintext
49 lines
1.3 KiB
Plaintext
---
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base_model:
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- {base_model}
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---
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# {model_name} GGUF
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Recommended way to run this model:
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```sh
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llama-server -hf {namespace}/{model_name}-GGUF --embeddings
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```
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Then the endpoint can be accessed at http://localhost:8080/embedding, for
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example using `curl`:
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```console
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curl --request POST \
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--url http://localhost:8080/embedding \
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--header "Content-Type: application/json" \
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--data '{{"input": "Hello embeddings"}}' \
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--silent
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```
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Alternatively, the `llama-embedding` command line tool can be used:
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```sh
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llama-embedding -hf {namespace}/{model_name}-GGUF --verbose-prompt -p "Hello embeddings"
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```
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#### embd_normalize
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When a model uses pooling, or the pooling method is specified using `--pooling`,
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the normalization can be controlled by the `embd_normalize` parameter.
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The default value is `2` which means that the embeddings are normalized using
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the Euclidean norm (L2). Other options are:
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* -1 No normalization
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* 0 Max absolute
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* 1 Taxicab
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* 2 Euclidean/L2
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* \>2 P-Norm
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This can be passed in the request body to `llama-server`, for example:
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```sh
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--data '{{"input": "Hello embeddings", "embd_normalize": -1}}' \
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```
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And for `llama-embedding`, by passing `--embd-normalize <value>`, for example:
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```sh
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llama-embedding -hf {namespace}/{model_name}-GGUF --embd-normalize -1 -p "Hello embeddings"
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```
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