Text Classification
Transformers
Safetensors
smollm3
agent-safety
tool-calling
long-context
Eval Results (legacy)
Instructions to use ProCreations/auto-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/auto-3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/auto-3b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProCreations/auto-3b") model = AutoModelForSequenceClassification.from_pretrained("ProCreations/auto-3b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Release auto-3b (SmolLM3-3B-Base approve/deny classifier, 98.03% on Approve-or-Deny)
58323da verified Download config.json from ProCreations/auto-3b: direct link, hf CLI and curl.
- Browser
- Download file 2.08 kB
-
https://huggingface.co/ProCreations/auto-3b/resolve/main/config.json
- Command line
-
hf download hf://ProCreations/auto-3b/config.json
-
curl -L -o config.json https://huggingface.co/ProCreations/auto-3b/resolve/main/config.json
2.08 kB
| { | |
| "architectures": [ | |
| "SmolLM3ForSequenceClassification" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": null, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 128001, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "id2label": { | |
| "0": "approve", | |
| "1": "deny" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 11008, | |
| "label2id": { | |
| "approve": 0, | |
| "deny": 1 | |
| }, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 65536, | |
| "mlp_bias": false, | |
| "model_type": "smollm3", | |
| "no_rope_layer_interval": 4, | |
| "no_rope_layers": [ | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 0 | |
| ], | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 36, | |
| "num_key_value_heads": 4, | |
| "pad_token_id": 128004, | |
| "pretraining_tp": 2, | |
| "problem_type": "single_label_classification", | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "rope_theta": 5000000.0, | |
| "rope_type": "default" | |
| }, | |
| "sliding_window": null, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.16.1", | |
| "use_cache": false, | |
| "use_sliding_window": false, | |
| "vocab_size": 128256 | |
| } | |