Generate.md

## 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