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add cl-nagoya/sup-simcse-ja-base embs

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	## create embeddings

	### multilingual-e5-small + passage

	```
	python datasets_to_embs.py \
	--target="data" \
	--model_name="intfloat/multilingual-e5-small" \
	--output_name="multilingual-e5-small-passage" \
	--input_prefix="passage: "
	python datasets_to_embs.py \
	--target="chunked" \
	--model_name="intfloat/multilingual-e5-small" \
	--output_name="multilingual-e5-small-passage" \
	--input_prefix="passage: "
	```

	### multilingual-e5-small + query

	```
	python datasets_to_embs.py \
	--target="data" \
	--model_name="intfloat/multilingual-e5-small" \
	--output_name="multilingual-e5-small-query" \
	--input_prefix="query: "
	python datasets_to_embs.py \
	--target="chunked" \
	--model_name="intfloat/multilingual-e5-small" \
	--output_name="multilingual-e5-small-query" \
	--input_prefix="query: "
	```

	## GLuCoSE-base-ja

	```
	python datasets_to_embs.py \
	--target="data" \
	--model_name="pkshatech/GLuCoSE-base-ja" \
	--output_name="GLuCoSE-base-ja"
	python datasets_to_embs.py \
	--target="chunked" \
	--model_name="pkshatech/GLuCoSE-base-ja" \
	--output_name="GLuCoSE-base-ja"
	```

	## cl-nagoya/sup-simcse-ja-base

	```
	python datasets_to_embs.py \
	--target="data" \
	--model_name="cl-nagoya/sup-simcse-ja-base" \
	--output_name="sup-simcse-ja-base"
	python datasets_to_embs.py \
	--target="chunked" \
	--model_name="cl-nagoya/sup-simcse-ja-base" \
	--output_name="sup-simcse-ja-base"
	```

	## create faiss indexes

	```
	python embs_to_faiss.py \
	--target="data" \
	--input_name="multilingual-e5-small-passage" \
	--use_gpu
	```

	### generate all by ./embs/

	```
	python all_embs_to_faiss.py --use_gpu
	```

	# XXX

	- 同じ output があったら skip する