Upload sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 ctranslate fp16 weights

README.md

@@ -23,13 +23,9 @@ pip install hf-hub-ctranslate2>=2.10.0 ctranslate2>=3.16.0
 # from transformers import AutoTokenizer
 model_name = "michaelfeil/ct2fast-paraphrase-multilingual-MiniLM-L12-v2"
 
-from hf_hub_ctranslate2 import EncoderCT2fromHfHub
-model = EncoderCT2fromHfHub(
-        # load in int8 on CUDA
-        model_name_or_path=model_name,
-        device="cuda",
-        compute_type="float16",
-        # tokenizer=AutoTokenizer.from_pretrained("{ORG}/{NAME}")
+from hf_hub_ctranslate2 import CT2SentenceTransformer
+model = CT2SentenceTransformer(
+    model_name, compute_type="int8_float16", device="cuda"
 )
 embeddings = model.encode(
     ["I like soccer", "I like tennis", "The eiffel tower is in Paris"],
@@ -47,9 +43,9 @@ and [hf-hub-ctranslate2>=2.10.0](https://github.com/michaelfeil/hf-hub-ctranslat
 - `compute_type=int8_float16` for `device="cuda"`
 - `compute_type=int8`  for `device="cpu"`
 
-Converted on 2023-06-16 using
+Converted on 2023-06-18 using
 ```
-ct2-transformers-converter --model sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 --output_dir ~/tmp-ct2fast-paraphrase-multilingual-MiniLM-L12-v2 --force --copy_files unigram.json config_sentence_transformers.json tokenizer.json modules.json README.md tokenizer_config.json sentence_bert_config.json special_tokens_map.json .gitattributes --quantization float16 --trust_remote_code
+ct2-transformers-converter --model sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 --output_dir ~/tmp-ct2fast-paraphrase-multilingual-MiniLM-L12-v2 --force --copy_files tokenizer.json sentence_bert_config.json README.md modules.json special_tokens_map.json config_sentence_transformers.json tokenizer_config.json unigram.json .gitattributes --trust_remote_code
 ```
 
 # Licence and other remarks:

model.bin

@@ -1,3 +1,3 @@
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-size 235315884
+oid sha256:03c883e3ae820352efa7873c2fbd04313278cda250f95ecec5804165ed92dbde
+size 470623404