Text Classification
Transformers
Safetensors
English
nli
cross-encoder
qwen3.5
reranker
image-text-to-text
Instructions to use AlexWortega/openjev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexWortega/openjev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AlexWortega/openjev")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlexWortega/openjev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download code/serving/prepare_v100_cuda.py from AlexWortega/openjev: direct link, hf CLI and curl.
- Browser
- Download file 1.69 kB
-
https://huggingface.co/AlexWortega/openjev/resolve/main/code/serving/prepare_v100_cuda.py
- Command line
-
hf download hf://AlexWortega/openjev/code/serving/prepare_v100_cuda.py
-
curl -L -o prepare_v100_cuda.py https://huggingface.co/AlexWortega/openjev/resolve/main/code/serving/prepare_v100_cuda.py
1.69 kB
| """Install NVIDIA's CUDA compiler redistributables into a private directory. | |
| No driver/system modifications. Archives are hash-verified against NVIDIA's | |
| versioned redistribution manifest before extraction. | |
| """ | |
| import argparse | |
| import hashlib | |
| import json | |
| from pathlib import Path | |
| import tarfile | |
| import urllib.request | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("root") | |
| ap.add_argument("--version", default="12.6.3") | |
| a = ap.parse_args() | |
| root = Path(a.root).resolve() | |
| root.mkdir(parents=True, exist_ok=True) | |
| url = "https://developer.download.nvidia.com/compute/cuda/redist/" | |
| manifest = json.load(urllib.request.urlopen(url + f"redistrib_{a.version}.json")) | |
| archives = root.parent / "cuda_archives" | |
| archives.mkdir(exist_ok=True) | |
| for package in ("cuda_nvcc", "cuda_cudart", "cuda_cccl", "cuda_nvrtc"): | |
| info = manifest[package]["linux-x86_64"] | |
| archive = archives / Path(info["relative_path"]).name | |
| if not archive.exists(): | |
| urllib.request.urlretrieve(url + info["relative_path"], archive) | |
| if hashlib.file_digest(archive.open("rb"), "sha256").hexdigest() != info["sha256"]: | |
| raise RuntimeError(f"Checksum mismatch: {archive}") | |
| with tarfile.open(archive) as source: | |
| for member in source.getmembers(): | |
| parts = Path(member.name).parts | |
| if len(parts) < 2: | |
| continue | |
| member.name = str(Path(*parts[1:])) | |
| source.extract(member, path=root, filter="data") | |
| print(f"Installed {package}: {info['sha256']}", flush=True) | |
| (root / f"redistrib_{a.version}.json").write_text(json.dumps(manifest, indent=2)) | |
| lib64 = root / "lib64" | |
| if not lib64.exists(): | |
| lib64.symlink_to("lib", target_is_directory=True) | |