Token Classification
Transformers
Safetensors
grt
ner
named-entity-recognition
rotational-transformer
givens-rotations
clifford-algebra
matterwave
Instructions to use MatterWaveAI/grt-30m-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatterWaveAI/grt-30m-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MatterWaveAI/grt-30m-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("MatterWaveAI/grt-30m-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,554 Bytes
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"angle_init_scale": 0.1,
"architectures": [
"GRTForTokenClassification"
],
"attention_dropout": 0.0,
"bos_token_id": 151643,
"coupling_init_mode": "diagonal",
"coupling_init_scale": 0.01,
"dtype": "float32",
"eos_token_id": 151643,
"ffn_n_experts": 0,
"ffn_n_rotations": 21,
"hidden_size": 256,
"id2label": {
"0": "O",
"1": "B-PER",
"2": "I-PER",
"3": "B-ORG",
"4": "I-ORG",
"5": "B-LOC",
"6": "I-LOC",
"7": "B-MISC",
"8": "I-MISC"
},
"initializer_range": 0.02,
"intermediate_size": 1024,
"label2id": {
"B-LOC": 5,
"B-MISC": 7,
"B-ORG": 3,
"B-PER": 1,
"I-LOC": 6,
"I-MISC": 8,
"I-ORG": 4,
"I-PER": 2,
"O": 0
},
"learnable_residual_gates": true,
"learnable_rope": true,
"log_magnitude_init": 0.0,
"max_position_embeddings": 2048,
"model_type": "grt",
"mor_delta_scale": 0.5,
"mor_mode": "direct",
"mor_router_mode": "rotational",
"mor_split_routers": false,
"mor_top_k": null,
"n_mixer_rotations": 1,
"n_qkv_rotations": 11,
"num_attention_heads": 4,
"num_hidden_layers": 12,
"num_labels": 9,
"output_scale_init": 30.0,
"pad_token_id": 151643,
"peri_ln": false,
"phase_init_scale": 0.1,
"pos_freq_base": 10000.0,
"residual_gate_mode": "bounded_depth",
"residual_norm_mode": "none",
"rope_placement": "stream",
"tie_word_embeddings": false,
"transformers_version": "5.21.0.dev0",
"use_cache": false,
"vocab_size": 151669
}
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