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Dictalm2.0 Instruct AWQ by dicta-il

 »  All LLMs  »  dicta-il  »  Dictalm2.0 Instruct AWQ   URL Share it on

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  Arxiv:2407.07080   4-bit   Awq   Base model:dicta-il/dictalm2.0 Base model:quantized:dicta-il/...   Conversational   En   He   Instruct   Instruction-tuned   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/dicta-il/dictalm2.0-instruct-AWQ 

Dictalm2.0 Instruct AWQ Benchmarks

LLME Score: 0.14642
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Dictalm2.0 Instruct AWQ (dicta-il/dictalm2.0-instruct-AWQ)
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Dictalm2.0 Instruct AWQ Parameters and Internals

Model Type 
instruct-tuned, text generation
Use Cases 
Limitations:
No moderation mechanisms in place.
Additional Notes 
Available as a chat template via the apply_chat_template method.
Supported Languages 
en (English), he (Hebrew)
Training Details 
Methodology:
Instruct fine-tuning using a variety of conversation datasets.
Model Architecture:
Zephyr-7B-beta
Input Output 
Input Format:
Expect instruction prompts to be surrounded by `[INST]` and `[/INST]` tokens.
Accepted Modalities:
text
LLM NameDictalm2.0 Instruct AWQ
Repository 🤗https://huggingface.co/dicta-il/dictalm2.0-instruct-AWQ 
Base Model(s)  dicta-il/dictalm2.0   dicta-il/dictalm2.0
Model Size7.3b
Required VRAM4.2 GB
Updated2026-02-04
Maintainerdicta-il
Model Typemistral
Instruction-BasedYes
Model Files  4.2 GB
Supported Languagesen he
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size33152
Torch Data Typefloat16

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Dictalm2.0 Instruct32K / 14.5 GB617624
Dictalm2.0 Instruct Fine Tuned32K / 14.5 GB55640
... Fine Tuned Alpaca Gpt4 Hebrew32K / 14.5 GB48440
Dictalm2 It Qa Fine Tune32K / 14.5 GB12097
Note: green Score (e.g. "73.2") means that the model is better than dicta-il/dictalm2.0-instruct-AWQ.

Rank the Dictalm2.0 Instruct AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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