| language: | |
| - en | |
| license: mit | |
| tags: | |
| - arcane | |
| - bart | |
| - mental-health | |
| - edge-ready | |
| pipeline_tag: text2text-generation | |
| # Arcane-BART | |
| **Arcane-BART** is a lightweight, efficient sequence-to-sequence model designed for fast mental health screening and real-time distress analysis. | |
| ## Overview | |
| - **Type**: Seq2Seq Transformer (~1.6 GB) | |
| - **Deployment**: Suitable for local CPU inference, containers, and edge backends. | |
| ## Inference Example | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| model_id = "ar3xop/arcane-bart" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_id) | |
| prompt = 'Consider this post: "The stress from examinations is unbearable." Question: What is the cause of stress?' | |
| inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True) | |
| output_ids = model.generate(**inputs, max_length=256) | |
| print(tokenizer.decode(output_ids[0], skip_special_tokens=True)) | |
| ``` | |