char-fork/llama.cpp
git clone https://git.t4t.associates/char-fork/llama.cpp
5d6688de0
char/aliceai-t5-moe
1--- 2base_model: 3- {base_model} 4--- 5# {model_name} GGUF 6 7Recommended way to run this model: 8 9```sh 10llama-server -hf {namespace}/{model_name}-GGUF --embeddings 11``` 12 13Then the endpoint can be accessed at http://localhost:8080/embedding, for 14example using `curl`: 15```console 16curl --request POST \ 17 --url http://localhost:8080/embedding \ 18 --header "Content-Type: application/json" \ 19 --data '{{"input": "Hello embeddings"}}' \ 20 --silent 21``` 22 23Alternatively, the `llama-embedding` command line tool can be used: 24```sh 25llama-embedding -hf {namespace}/{model_name}-GGUF --verbose-prompt -p "Hello embeddings" 26``` 27 28#### embd_normalize 29When a model uses pooling, or the pooling method is specified using `--pooling`, 30the normalization can be controlled by the `embd_normalize` parameter. 31 32The default value is `2` which means that the embeddings are normalized using 33the Euclidean norm (L2). Other options are: 34* -1 No normalization 35* 0 Max absolute 36* 1 Taxicab 37* 2 Euclidean/L2 38* \>2 P-Norm 39 40This can be passed in the request body to `llama-server`, for example: 41```sh 42 --data '{{"input": "Hello embeddings", "embd_normalize": -1}}' \ 43``` 44 45And for `llama-embedding`, by passing `--embd-normalize <value>`, for example: 46```sh 47llama-embedding -hf {namespace}/{model_name}-GGUF --embd-normalize -1 -p "Hello embeddings" 48```