From c8c1186b133077a3347b3a06f947ebd3093c030f Mon Sep 17 00:00:00 2001 From: alabulei1 Date: Tue, 4 Feb 2025 14:33:24 +0800 Subject: [PATCH] Update csv.md --- docs/knowledge-bases/how-to/csv.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/knowledge-bases/how-to/csv.md b/docs/knowledge-bases/how-to/csv.md index 66e8e9e..043355c 100644 --- a/docs/knowledge-bases/how-to/csv.md +++ b/docs/knowledge-bases/how-to/csv.md @@ -83,7 +83,7 @@ Next, you can run the program by passing a collection name, vector dimension, an The `--ctx_size` option matches the embedding model's context window size, which in this case is 8192 tokens allowing it to process long sections of text. Make sure that Qdrant is running on your local machine. The model is preloaded under the name embedding. The wasm app then uses the embedding model to create the 768-dimension vectors from `paris.csv` and saves them into the default collection. ``` -curl -LO https://huggingface.co/datasets/gaianet/eigenlayerKannan/resolve/main/eigen_vectors.csv +curl -LO https://huggingface.co/datasets/gaianet/paris/resolve/main/paris.csv wasmedge --dir .:. \ --nn-preload embedding:GGML:AUTO:nomic-embed-text-v1.5.f16.gguf \