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feat(transformers): add embeddings with Automodel (#1308)
* Update huggingface.py Switch SentenceTransformer for AutoModel in order to set trust_remote_code needed to use the encode method with embeddings models like jinai-v2 Signed-off-by: Lucas Hänke de Cansino <lhc@next-boss.eu> * feat(transformers): split in separate backend Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Lucas Hänke de Cansino <lhc@next-boss.eu> Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Lucas Hänke de Cansino <lhc@next-boss.eu>
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@ -704,7 +704,7 @@ var _ = Describe("API test", func() {
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})
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Context("External gRPC calls", func() {
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It("calculate embeddings with huggingface", func() {
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It("calculate embeddings with sentencetransformers", func() {
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if runtime.GOOS != "linux" {
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Skip("test supported only on linux")
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}
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