Instructions to use VijayRam1812/content-classifier-gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VijayRam1812/content-classifier-gemma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VijayRam1812/content-classifier-gemma")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VijayRam1812/content-classifier-gemma") model = AutoModelForSequenceClassification.from_pretrained("VijayRam1812/content-classifier-gemma") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_sliding_window_pattern": 6, | |
| "architectures": [ | |
| "Gemma3TextForSequenceClassification" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "attn_logit_softcapping": null, | |
| "bos_token_id": 2, | |
| "cache_implementation": "hybrid", | |
| "dtype": "bfloat16", | |
| "eos_token_id": [ | |
| 1, | |
| 106 | |
| ], | |
| "final_logit_softcapping": null, | |
| "head_dim": 256, | |
| "hidden_activation": "gelu_pytorch_tanh", | |
| "hidden_size": 1152, | |
| "id2label": { | |
| "0": "LABEL_0" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6912, | |
| "label2id": { | |
| "LABEL_0": 0 | |
| }, | |
| "layer_types": [ | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention" | |
| ], | |
| "max_position_embeddings": 32768, | |
| "model_type": "gemma3_text", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 26, | |
| "num_key_value_heads": 1, | |
| "pad_token_id": 0, | |
| "query_pre_attn_scalar": 256, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "full_attention": { | |
| "rope_theta": 1000000, | |
| "rope_type": "default" | |
| }, | |
| "sliding_attention": { | |
| "rope_theta": 10000, | |
| "rope_type": "default" | |
| } | |
| }, | |
| "sliding_window": 512, | |
| "sliding_window_pattern": 6, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.2.0", | |
| "use_bidirectional_attention": false, | |
| "use_cache": false, | |
| "vocab_size": 262144 | |
| } | |