Visual Document Retrieval
Safetensors
sentence-transformers
colpali-engine
qwen3_5
vision-language
colbert
late-interaction
multi-vector
vidore
document-retrieval
multimodal
Instructions to use tencent/EVIE-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tencent/EVIE-8B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tencent/EVIE-8B") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
File size: 1,340 Bytes
315e4cf | 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 38 39 40 41 42 43 44 45 46 47 48 49 | """Refuse to write train/eval/compress products into the Python venv."""
from __future__ import annotations
import os
import sys
from pathlib import Path
def venv_roots() -> list[Path]:
roots: list[Path] = []
venv = os.environ.get("VIRTUAL_ENV")
if venv:
roots.append(Path(venv))
evie = os.environ.get("EVIE_ROOT")
if evie:
for name in ("env", "venv", ".venv", "train-env"):
roots.append(Path(evie) / name)
prefix = Path(sys.prefix)
if (prefix / "pyvenv.cfg").is_file():
roots.append(prefix)
out: list[Path] = []
seen: set[Path] = set()
for raw in roots:
try:
resolved = raw.resolve()
except OSError:
continue
if resolved in seen:
continue
seen.add(resolved)
out.append(resolved)
return out
def forbid_venv_path(path: str | Path, label: str) -> Path:
path = Path(path).expanduser().resolve()
for root in venv_roots():
try:
path.relative_to(root)
except ValueError:
continue
raise ValueError(
f"{label} must not sit inside the Python env ({root}): {path}. "
"Checkpoints -> $RUNS_DIR ($EVIE_ROOT/runs); "
"HF caches -> $EVIE_ROOT/.cache; never $EVIE_ROOT/env."
)
return path
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