Sentence Similarity
sentence-transformers
Safetensors
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use rounit786757/e5-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rounit786757/e5-large-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rounit786757/e5-large-v2") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 1,268 Bytes
fe1a8a0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | # Checkpoint System
This directory stores runtime checkpoint files used to resume index building after interruptions.
## Files
| File | Purpose |
|------|---------|
| `experiences_checkpoint.json` | Saves parsed catalog records after data ingestion (from `scripts/build_index.py`) |
| `embedding_checkpoint.npy` | Saves partial E5 embeddings during batch encoding (from `core/indexer.py`) |
## Auto-Checkpoint Behavior
### Experiences Checkpoint
- **Created** after all data files are parsed into memory
- **Resume** - if `experiences_checkpoint.json` exists on next run, data ingestion is skipped entirely
- **Removed** automatically after a successful full build
### Embedding Checkpoint
- **Created** after each batch during the E5 encoding loop
- **Resume** - if `embedding_checkpoint.npy` exists, encoding resumes from the last completed batch
- **Removed** automatically after a successful full build
## Manual Control
To force a complete fresh build from scratch:
```powershell
# Remove checkpoints manually
Remove-Item -LiteralPath "index\experiences_checkpoint.json" -ErrorAction SilentlyContinue
Remove-Item -LiteralPath "index\embedding_checkpoint.npy" -ErrorAction SilentlyContinue
```
Then re-run:
```powershell
python scripts/build_index.py
```
|