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Sentence Transformers Aliasing (#3541)

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The sentence transformers was a dup of the HF one. 

This is a breaking change (model_name vs. model) for anyone using
`SentenceTransformerEmbeddings(model="some/nondefault/model")`, but
since it was landed only this week it seems better to do this now rather
than doing a wrapper.
This commit is contained in:
Zander Chase
2023-04-25 23:29:20 -07:00
committed by GitHub
parent 603ea75bcd
commit d6d697a41b
2 changed files with 18 additions and 75 deletions
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30
docs/modules/models/text_embedding/examples/sentence_transformers.ipynb
View File

@@ -8,12 +8,14 @@
"source": [
"# Sentence Transformers Embeddings\n",
"\n",
"Let's generate embeddings using the [SentenceTransformers](https://www.sbert.net/) integration. SentenceTransformers is a python package that can generate text and image embeddings, originating from [Sentence-BERT](https://arxiv.org/abs/1908.10084)"
"[SentenceTransformers](https://www.sbert.net/) embeddings are called using the `HuggingFaceEmbeddings` integration. We have also added an alias for `SentenceTransformerEmbeddings` for users who are more familiar with directly using that package.\n",
"\n",
"SentenceTransformers is a python package that can generate text and image embeddings, originating from [Sentence-BERT](https://arxiv.org/abs/1908.10084)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 1,
"id": "06c9f47d",
"metadata": {},
"outputs": [
@@ -21,10 +23,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
"To disable this warning, you can either:\n",
"\t- Avoid using `tokenizers` before the fork if possible\n",
"\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
"\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.1.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
]
}
],
@@ -34,27 +35,28 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 2,
"id": "861521a9",
"metadata": {},
"outputs": [],
"source": [
"from langchain.embeddings import SentenceTransformerEmbeddings "
"from langchain.embeddings import HuggingFaceEmbeddings, SentenceTransformerEmbeddings "
]
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "ff9be586",
"metadata": {},
"outputs": [],
"source": [
"embeddings = SentenceTransformerEmbeddings(model=\"all-MiniLM-L6-v2\")"
"embeddings = HuggingFaceEmbeddings(model_name=\"all-MiniLM-L6-v2\")\n",
"# Equivalent to SentenceTransformerEmbeddings(model_name=\"all-MiniLM-L6-v2\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 4,
"id": "d0a98ae9",
"metadata": {},
"outputs": [],
@@ -64,7 +66,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 5,
"id": "5d6c682b",
"metadata": {},
"outputs": [],
@@ -74,7 +76,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 6,
"id": "bb5e74c0",
"metadata": {},
"outputs": [],
@@ -107,7 +109,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.2"
"version": "3.8.16"
},
"vscode": {
"interpreter": {