Instructions to use devangb4/prm-qwen3-8b-seqcls-final1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devangb4/prm-qwen3-8b-seqcls-final1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devangb4/prm-qwen3-8b-seqcls-final1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devangb4/prm-qwen3-8b-seqcls-final1") model = AutoModelForSequenceClassification.from_pretrained("devangb4/prm-qwen3-8b-seqcls-final1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from devangb4/prm-qwen3-8b-seqcls-final1: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/devangb4/prm-qwen3-8b-seqcls-final1/resolve/main/tokenizer.json
- Command line
-
hf download hf://devangb4/prm-qwen3-8b-seqcls-final1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/devangb4/prm-qwen3-8b-seqcls-final1/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- e1b0090408ce2804b49478b75161d644131c4558404098911b8b54a8351668ac
- Size of remote file:
- 11.4 MB
- SHA256:
- 82f51bc8dcbe99231aa64245532e22af8da1299bdff70497c78d674db2472c6a
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