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Model: YonatanDavidov/qasem-he-dictalm2-full Source: Original Platform
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README.md
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---
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base_model: dicta-il/dictalm2.0-instruct
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library_name: transformers
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license: mit
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language:
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- he
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tags:
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- qasem
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- hebrew
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- causal-lm
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- semantic-parsing
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datasets:
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- biu-nlp/Multilingual_QASem_Datasets
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pipeline_tag: text-generation
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---
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# QASem Hebrew Full Model (DictaLM 2.0)
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This model performs **QA-based semantic parsing (QASem) in Hebrew**.
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## Overview
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This repository provides a **fully fine-tuned model** for performing **QA-based semantic parsing (QASem) in Hebrew**.
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QASem represents predicate–argument structure using **natural-language question–answer pairs**, rather than predefined semantic role labels. This makes the representation more interpretable and flexible across languages.
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The model is based on:
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**Base model:** `dicta-il/dictalm2.0-instruct`
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and was fully fine-tuned for QA-based semantic parsing.
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## ✨ Why this model matters
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Traditional semantic role labeling methods rely on fixed label schemas and costly expert annotation.
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This model takes a different approach by:
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- Representing semantics using **natural-language question–answer pairs**
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- Enabling **automatic dataset construction** via cross-lingual projection
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- Supporting **scalable semantic parsing across languages**
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- Achieving strong performance with **efficient fine-tuned models**
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This makes it possible to build semantic parsers for new languages with minimal cost.
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## Use Cases
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This model can be used for:
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- Research in **QA-based semantic parsing (QASem)** and semantic representation learning
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- Extraction of **predicate–argument structures** from Hebrew text
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- Automatic **dataset creation** for training semantic models in new languages
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- Downstream NLP applications such as:
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- Information extraction
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- Text understanding
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- Factuality and attribution evaluation
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## Language
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- Hebrew 🇮🇱
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## Training Data
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The model was trained on the **Multilingual QASem Dataset**:
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👉 https://huggingface.co/datasets/biu-nlp/Multilingual_QASem_Datasets
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The dataset includes:
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- Automatically generated QASem annotations
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- Train / Development / Test splits
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- Multiple languages: **French, Hebrew, Russian**
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- Tens of thousands of QA pairs per language
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The data was constructed using a cross-lingual projection approach, ensuring scalability across languages.
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## 📄 Associated Work
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This model and the underlying dataset are introduced in:
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[Effective QA-Driven Annotation of Predicate-Argument Relations Across Languages](https://aclanthology.org/2026.eacl-long.112/).
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The paper presents the full methodology, dataset construction process, and evaluation across multiple languages.
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## 🚀 Quick Start (Recommended)
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### Using the XQASem Parser
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For a simple and structured interface, you can use the XQASem parser.
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### Installation
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```bash
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pip install xqasem
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```
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### Basic Example
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```python
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from xqasem import XQasemParser
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parser = XQasemParser.from_language("he")
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sentences = [
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"המומחים הדגישו שהאלגוריתם החדש מאיץ משמעותית את עיבוד הבקשות המורכבות."
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]
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df = parser(sentences)
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print(df)
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```
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## Output Format
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The model produces structured predicate–argument representations in the form of:
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- A predicate (verb or nominal)
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- A natural-language question
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- A corresponding answer span from the sentence
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This structure can be easily converted into tabular or JSON format for downstream use.
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### Example Output
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| sentence | predicate | predicate_type | question | answer |
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| --- | --- | --- | --- | --- |
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| המומחים הדגישו שהאלגוריתם החדש מאיץ משמעותית את עיבוד הבקשות המורכבות. | הדגישו | verb | מי הדגיש משהו? | המומחים |
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| המומחים הדגישו שהאלגוריתם החדש מאיץ משמעותית את עיבוד הבקשות המורכבות. | הדגישו | verb | מה מישהו הדגיש? | שהאלגוריתם החדש מאיץ משמעותית את עיבוד הבקשות המורכבות |
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| המומחים הדגישו שהאלגוריתם החדש מאיץ משמעותית את עיבוד הבקשות המורכבות. | מאיץ | verb | מה מאיץ משהו? | האלגוריתם החדש |
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| המומחים הדגישו שהאלגוריתם החדש מאיץ משמעותית את עיבוד הבקשות המורכבות. | מאיץ | verb | מה משהו מאיץ? | את עיבוד הבקשות המורכבות |
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👉 For more details and advanced usage, see the project repository:
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https://github.com/JohnnieDavidov/xqasem
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## Manual Model Loading (Advanced)
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "YonatanDavidov/qasem-he-dictalm2-full"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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```
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## Limitations
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- Performance may degrade on out-of-domain text
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- Complex or ambiguous predicates may lead to inconsistent outputs
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- The model is optimized for QASem-style generation and not for general-purpose text generation
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## 📄 Citation
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If you use this model, please cite our work:
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```
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@inproceedings{davidov-etal-2026-effective,
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title = "Effective {QA}-Driven Annotation of Predicate{--}Argument Relations Across Languages",
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author = "Davidov, Jonathan and
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Slobodkin, Aviv and
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Klein, Shmuel Tomi and
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Tsarfaty, Reut and
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Dagan, Ido and
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Klein, Ayal",
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editor = "Demberg, Vera and
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Inui, Kentaro and
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Marquez, Llu{\'i}s",
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booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
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month = mar,
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year = "2026",
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address = "Rabat, Morocco",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2026.eacl-long.112/",
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doi = "10.18653/v1/2026.eacl-long.112",
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pages = "2484--2502",
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ISBN = "979-8-89176-380-7",
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}
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```
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config.json
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"document_attention": true,
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"hidden_size": 4096,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.50.0.dev0",
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"use_cache": false,
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"vocab_size": 33152
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}
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|
||||
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|
||||
}
|
||||
}
|
||||
24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "</s>",
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
275995
tokenizer.json
Normal file
275995
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:4be9ca9094291607e3f9943ff0a0dfd3ceb35d2fcb383aac560a4399725918b8
|
||||
size 512736
|
||||
44
tokenizer_config.json
Normal file
44
tokenizer_config.json
Normal file
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"add_prefix_space": null,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]\n' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token + ' ' }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"extra_special_tokens": {},
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "</s>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user