Text Classification
Transformers
Safetensors
dihya
feature-extraction
berber
amazigh
kabyle
tashelhit
tarifit
tamasheq
tamazight
shawiya
language-identification
conformal-prediction
low-resource
custom_code
Eval Results (legacy)
Instructions to use agbalu/Dihya-5M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agbalu/Dihya-5M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agbalu/Dihya-5M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("agbalu/Dihya-5M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "DihyaForSequenceClassification" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_dihya.DihyaConfig", | |
| "AutoModel": "modeling_dihya.DihyaForSequenceClassification", | |
| "AutoModelForSequenceClassification": "modeling_dihya.DihyaForSequenceClassification" | |
| }, | |
| "byte_offset": 2, | |
| "classes": [ | |
| "kab_Latn", | |
| "shi_Latn", | |
| "rif_Latn", | |
| "taq_Latn", | |
| "tzm_Latn", | |
| "shy_Latn", | |
| "NOT_AMAZIGH" | |
| ], | |
| "conv_dim": 128, | |
| "conv_kernels": [ | |
| 3, | |
| 5, | |
| 7 | |
| ], | |
| "dropout_prob": 0.1, | |
| "hidden_size": 256, | |
| "id2label": { | |
| "0": "kab_Latn", | |
| "1": "shi_Latn", | |
| "2": "rif_Latn", | |
| "3": "taq_Latn", | |
| "4": "tzm_Latn", | |
| "5": "shy_Latn", | |
| "6": "NOT_AMAZIGH" | |
| }, | |
| "intermediate_size": 704, | |
| "label2id": { | |
| "NOT_AMAZIGH": 6, | |
| "kab_Latn": 0, | |
| "rif_Latn": 2, | |
| "shi_Latn": 1, | |
| "shy_Latn": 5, | |
| "taq_Latn": 3, | |
| "tzm_Latn": 4 | |
| }, | |
| "logit_scale": 24.0, | |
| "max_position_embeddings": 256, | |
| "model_type": "dihya", | |
| "num_attention_heads": 8, | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 0, | |
| "prior_shift": [ | |
| -0.6155660152435303, | |
| -0.5855244994163513, | |
| -1.1106044054031372, | |
| -1.2838202714920044, | |
| -2.21260666847229, | |
| -2.5694897174835205, | |
| -0.8174624443054199 | |
| ], | |
| "q_hat": 0.997931957244873, | |
| "rms_norm_eps": 1e-06, | |
| "rope_theta": 10000.0, | |
| "target_coverage": 0.99, | |
| "transformers_version": "5.12.1", | |
| "unk_token_id": 1, | |
| "vocab_size": 258 | |
| } | |