From a14aab8ef4a6d9b5aa6e7e473b65a7266f67cebe Mon Sep 17 00:00:00 2001 From: NirantK Date: Wed, 18 Oct 2023 20:48:51 +0530 Subject: [PATCH 1/3] * refactor(Getting Started.ipynb): simplify code for initializing DefaultEmbedding class --- docs/Getting Started.ipynb | 35 ++++++++++------------------------- 1 file changed, 10 insertions(+), 25 deletions(-) diff --git a/docs/Getting Started.ipynb b/docs/Getting Started.ipynb index 750226f..7cae56f 100644 --- a/docs/Getting Started.ipynb +++ b/docs/Getting Started.ipynb @@ -38,18 +38,11 @@ "id": "b61c6552", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "torch.Size([384])\n" + "(384,)\n" ] } ], @@ -64,9 +57,9 @@ " \"This is an example document.\",\n", " \"fastembed is supported by and maintained by Qdrant.\",\n", "]\n", - "# Initialize the DefaultEmbedding class with the desired parameters\n", - "embedding_model = DefaultEmbedding(model_name=\"BAAI/bge-small-en\", max_length=512)\n", - "embeddings: List[np.ndarray] = embedding_model.embed(documents)\n", + "# Initialize the DefaultEmbedding class\n", + "embedding_model = DefaultEmbedding()\n", + "embeddings: List[np.ndarray] = list(embedding_model.embed(documents))\n", "print(embeddings[0].shape)" ] }, @@ -97,7 +90,7 @@ "source": [ "from typing import List\n", "import numpy as np\n", - "from fastembed.embedding import DefaultEmbedding as Embedding" + "from fastembed.embedding import DefaultEmbedding" ] }, { @@ -171,20 +164,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "8013eee9", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.\n" - ] - } - ], + "outputs": [], "source": [ - "embeddings: List[np.ndarray] = embedding_model.embed(documents)" + "embeddings: List[np.ndarray] = list(embedding_model.embed(documents))" ] }, { @@ -197,7 +182,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "id": "0d8c8e08", "metadata": {}, "outputs": [ @@ -205,7 +190,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "torch.Size([384])\n" + "(384,)\n" ] } ], From fd55b46f4b6f1beba217732d2bfd86dd341f1054 Mon Sep 17 00:00:00 2001 From: NirantK Date: Wed, 18 Oct 2023 20:49:01 +0530 Subject: [PATCH 2/3] * fix(embedding.py): update default model_name to "BAAI/bge-small-en-v1.5" --- fastembed/embedding.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/fastembed/embedding.py b/fastembed/embedding.py index ae9ac78..71cfadc 100644 --- a/fastembed/embedding.py +++ b/fastembed/embedding.py @@ -403,7 +403,7 @@ class FlagEmbedding(Embedding): def __init__( self, - model_name: str = "BAAI/bge-small-en", + model_name: str = "BAAI/bge-small-en-v1.5", max_length: int = 512, cache_dir: str = None, threads: int = None, From b61f8a48cc85ff2f15ead3135cc9047d872fedcb Mon Sep 17 00:00:00 2001 From: NirantK Date: Wed, 18 Oct 2023 20:49:31 +0530 Subject: [PATCH 3/3] Update to v1.5 model --- .../examples/FastEmbed_vs_HF_Comparison.ipynb | 33 +++++++++---------- 1 file changed, 16 insertions(+), 17 deletions(-) diff --git a/docs/examples/FastEmbed_vs_HF_Comparison.ipynb b/docs/examples/FastEmbed_vs_HF_Comparison.ipynb index 07a38e2..5130c8c 100644 --- a/docs/examples/FastEmbed_vs_HF_Comparison.ipynb +++ b/docs/examples/FastEmbed_vs_HF_Comparison.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -42,7 +42,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -51,7 +51,7 @@ "12" ] }, - "execution_count": 3, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -85,7 +85,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -94,7 +94,7 @@ "torch.Size([12, 384])" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -103,7 +103,6 @@ "class HF:\n", " \"\"\"\n", " HuggingFace Transformer implementation of FlagEmbedding\n", - " Based on https://huggingface.co/BAAI/bge-base-en\n", " \"\"\"\n", "\n", " def __init__(self, model_id: str):\n", @@ -117,7 +116,7 @@ " sentence_embeddings = F.normalize(sentence_embeddings)\n", " return sentence_embeddings\n", "\n", - "hf = HF(model_id=\"BAAI/bge-small-en\")\n", + "hf = HF(model_id=\"BAAI/bge-small-en-v1.5\")\n", "hf.embed(documents).shape" ] }, @@ -132,7 +131,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -152,15 +151,15 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Huggingface Transformers (Average, Max, Min): (0.06628990173339844, 0.06881093978881836, 0.06376886367797852)\n", - "FastEmbed (Average, Max, Min): (0.037211060523986816, 0.03802299499511719, 0.036399126052856445)\n" + "Huggingface Transformers (Average, Max, Min): (0.0635751485824585, 0.06534004211425781, 0.06181025505065918)\n", + "FastEmbed (Average, Max, Min): (0.03929698467254639, 0.039344072341918945, 0.03924989700317383)\n" ] } ], @@ -199,12 +198,12 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -261,24 +260,24 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/b4/grpbcmrd36gc7q5_11whbn540000gn/T/ipykernel_34880/1522845950.py:7: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/torch/csrc/utils/tensor_new.cpp:248.)\n", + "/var/folders/b4/grpbcmrd36gc7q5_11whbn540000gn/T/ipykernel_32737/1522845950.py:7: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/torch/csrc/utils/tensor_new.cpp:248.)\n", " calculate_cosine_similarity(hf.embed(documents), Tensor(list(embedding_model.embed(documents))))\n" ] }, { "data": { "text/plain": [ - "0.9999997019767761" + "0.9165658950805664" ] }, - "execution_count": 13, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }