Zero-Shot Classification
Transformers
Safetensors
English
qwen3_5_text
text-generation
scientific-papers
taxonomy
classification
science-of-science
probabilities
qwen3_5
Instructions to use maximerivest/paper-classifier-2B-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maximerivest/paper-classifier-2B-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="maximerivest/paper-classifier-2B-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("maximerivest/paper-classifier-2B-v2") model = AutoModelForCausalLM.from_pretrained("maximerivest/paper-classifier-2B-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download release.json from maximerivest/paper-classifier-2B-v2: direct link, hf CLI and curl.
- Browser
- Download file 510 Bytes
-
https://huggingface.co/maximerivest/paper-classifier-2B-v2/resolve/main/release.json
- Command line
-
hf download hf://maximerivest/paper-classifier-2B-v2/release.json
-
curl -L -o release.json https://huggingface.co/maximerivest/paper-classifier-2B-v2/resolve/main/release.json
510 Bytes
| { | |
| "release_version": "2", | |
| "weight_sha256": "08f5352f876985df04f95da4ef590dd8b03712a03498876f7907143aa69bf9e9", | |
| "stored_parameters": 2390384448, | |
| "weight_bytes": 4780810864, | |
| "dtype": "bfloat16", | |
| "architecture": "Qwen3_5ForCausalLM", | |
| "format": "list-first-filler-v1", | |
| "library_versions_tested": { | |
| "transformers": "5.3.0", | |
| "torch": "2.11.0", | |
| "vllm": "0.29.0" | |
| }, | |
| "note": "The size tier follows the upstream model name; exported weights include an untied vocabulary-output matrix." | |
| } | |