Model reference · open weights

dictabert-morph

Embeddings dicta-il Embeddings 1 build Open weights 2k dl/mo

dictabert-morph is an open-weight embedding model from dicta-il. dictabert-morph (FP32) weighs 369 MB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • dictabert-morph is a feature-extraction model developed by dicta-il for morphological tagging in Hebrew.
  • It contains 184M parameters and supports a context length of 512 tokens.
  • The model is released under the cc-by-4.0 licence.

Summary of the dicta-il/dictabert-morph model card, 2026-10-01

What it is

Released bydicta-il
Released2023-08-29
Parameters184M
VRAM369 MB for the weights

What it runs on

Memory and cards for dictabert-morph (FP32)

369 MBweights, file size
1.1 GBruntime overhead
CardRunsMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What dicta-il says about dictabert-morph

Read the model card

State-of-the-art language model for Hebrew, released here.

This is the fine-tuned model for the morphological tagging task.

For the bert-base models for other tasks, see here.

Sample usage:

from transformers import AutoModel, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained('dicta-il/dictabert-morph')
model = AutoModel.from_pretrained('dicta-il/dictabert-morph', trust_remote_code=True)

model.eval()

sentence = 'בשנת 1948 השלים אפרים קישון את לימודיו בפיסול מתכת ובתולדות האמנות והחל לפרסם מאמרים הומוריסטיים'
print(model.predict([sentence], tokenizer))

Output:

[{
	"text": "בשנת 1948 השלים אפרים קישון את לימודיו בפיסול מתכת ובתולדות האמנות והחל לפרסם מאמרים הומוריסטיים",
	"tokens": [{
		"token": "בשנת",
		"pos": "NOUN",
		"feats": {
			"Gender": "Fem",
			"Number": "Sing"
		},
		"prefixes": ["ADP"],
		"suffix": false
	}, {
		"token": "1948",
		"pos": "NUM",
		"feats": {},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "השלים",
		"pos": "VERB",
		"feats": {
			"Gender": "Masc",
			"Number": "Sing",
			"Person": "3",
			"Tense": "Past"
		},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "אפרים",
		"pos": "PROPN",
		"feats": {},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "קישון",
		"pos": "PROPN",
		"feats": {},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "את",
		"pos": "ADP",
		"feats": {},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "לימודיו",
		"pos": "NOUN",
		"feats": {
			"Gender": "Masc",
			"Number": "Plur"
		},
		"prefixes": [],
		"suffix": "PRON",
		"suffix_feats": {
			"Gender": "Masc",
			"Number": "Sing",
			"Person": "3"
		}
	}, {
		"token": "בפיסול",
		"pos": "NOUN",
		"feats": {
			"Gender": "Masc",
			"Number": "Sing"
		},
		"prefixes": ["ADP"],
		"suffix": false
	}, {
		"token": "מתכת",
		"pos": "NOUN",
		"feats": {
			"Gender": "Fem",
			"Number": "Sing"
		},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "ובתולדות",
		"pos": "NOUN",
		"feats": {
			"Gender": "Fem",
			"Number": "Plur"
		},
		"prefixes": ["CCONJ", "ADP"],
		"suffix": false
	}, {
		"token": "האמנות",
		"pos": "NOUN",
		"feats": {
			"Gender": "Fem",
			"Number": "Sing"
		},
		"prefixes": ["DET"],
		"suffix": false
	}, {
		"token": "והחל",
		"pos": "VERB",
		"feats": {
			"Gender": "Masc",
			"Number": "Sing",
			"Person": "3",
			"Tense": "Past"
		},
		"prefixes": ["CCONJ"],
		"suffix": false
	}, {
		"token": "לפרסם",
		"pos": "VERB",
		"feats": {},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "מאמרים",
		"pos": "NOUN",
		"feats": {
			"Gender": "Masc",
			"Number": "Plur"
		},
		"prefixes": [],
		"suffix": false
	}, {
		"token": "הומוריסטיים",
		"pos": "ADJ",
		"feats": {
			"Gender": "Masc",
			"Number": "Plur"
		},
		"prefixes": [],
		"suffix": false
	}]
}]

Citation

If you use DictaBERT in your research, please cite DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew

BibTeX:

@misc{shmidman2023dictabert,
      title={DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew},
      author={Shaltiel Shmidman and Avi Shmidman and Moshe Koppel},
      year={2023},
      eprint={2308.16687},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

License

Shield: CC BY 4.0

This work is licensed under a Creative Commons Attribution 4.0 International License.

CC BY 4.0

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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