Zero-Shot Classification
PEFT
Safetensors
English
assay
decision-model
calibrated
conformal-prediction
text-classification
structured-output
Instructions to use Berk/assay-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Berk/assay-8b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B-Base") model = PeftModel.from_pretrained(base_model, "Berk/assay-8b") - Notebooks
- Google Colab
- Kaggle
Download train_args.json from Berk/assay-8b: direct link, hf CLI and curl.
- Browser
- Download file 566 Bytes
-
https://huggingface.co/Berk/assay-8b/resolve/main/train_args.json
- Command line
-
hf download hf://Berk/assay-8b/train_args.json
-
curl -L -o train_args.json https://huggingface.co/Berk/assay-8b/resolve/main/train_args.json
566 Bytes
| { | |
| "base": "Qwen/Qwen3-8B-Base", | |
| "data": "data/v4", | |
| "out": "runs/assay-8b", | |
| "lora_r": 16, | |
| "lora_alpha": 32, | |
| "lr": 5e-05, | |
| "head_lr": 0.001, | |
| "epochs": 1.0, | |
| "batch_size": 4, | |
| "grad_accum": 2, | |
| "warmup": 0.03, | |
| "weight_decay": 0.0, | |
| "evidence_weight": 0.5, | |
| "score_sigma": 0.5, | |
| "hard_targets": false, | |
| "content_term": false, | |
| "max_state_tokens": 1024, | |
| "limit": null, | |
| "eval_every": 0, | |
| "log_every": 20, | |
| "seed": 0, | |
| "no_gradient_checkpointing": false, | |
| "checkpoint_every": 500, | |
| "resume": true, | |
| "quant": null, | |
| "eval_batch_size": 8 | |
| } |