llama : add reranking support (#9510)

* py : add XLMRobertaForSequenceClassification [no ci]

* py : fix scalar-tensor conversion [no ci]

* py : fix position embeddings chop [no ci]

* llama : read new cls tensors [no ci]

* llama : add classigication head (wip) [no ci]

* llama : add "rank" pooling type

ggml-ci

* server : add rerank endpoint

ggml-ci

* llama : aboud ggml_repeat during classification

* rerank : cleanup + comments

* server : accept /rerank endpoint in addition to /v1/rerank [no ci]

* embedding : parse special tokens

* jina : support v1 reranker

* vocab : minor style

ggml-ci

* server : initiate tests for later

ggml-ci

* server : add docs

* llama : add comment [no ci]

* llama : fix uninitialized tensors

* ci : add rerank tests

ggml-ci

* add reranking test

* change test data

* Update examples/server/server.cpp

Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>

* add `--reranking` argument

* update server docs

* llama : fix comment [no ci]

ggml-ci

---------

Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
This commit is contained in:
Georgi Gerganov 2024-09-28 17:42:03 +03:00 committed by GitHub
parent 1b2f992cd2
commit f4d2b8846a
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GPG key ID: B5690EEEBB952194
18 changed files with 602 additions and 56 deletions

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@ -135,7 +135,7 @@ int main(int argc, char ** argv) {
// tokenize the prompts and trim
std::vector<std::vector<int32_t>> inputs;
for (const auto & prompt : prompts) {
auto inp = ::llama_tokenize(ctx, prompt, true, false);
auto inp = ::llama_tokenize(ctx, prompt, true, true);
if (inp.size() > n_batch) {
LOG_ERR("%s: number of tokens in input line (%lld) exceeds batch size (%lld), increase batch size and re-run\n",
__func__, (long long int) inp.size(), (long long int) n_batch);
@ -234,6 +234,11 @@ int main(int argc, char ** argv) {
}
LOG("\n");
}
} else if (pooling_type == LLAMA_POOLING_TYPE_RANK) {
for (int j = 0; j < n_embd_count; j++) {
// NOTE: if you change this log - update the tests in ci/run.sh
LOG("rerank score %d: %8.3f\n", j, emb[j * n_embd]);
}
} else {
// print the first part of the embeddings or for a single prompt, the full embedding
for (int j = 0; j < n_prompts; j++) {