dictalm2.0-instruct-GGUF

tensorblock/dictalm2.0-instruct-GGUF

dictalm2.0-instruct-GGUF is a text generation model from tensorblock. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.

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Downloads · 30 days

2% of all-time downloads

All-time downloads

2.5K

Public

Repo size

54.7 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.gguf6.2 GB · 100%

At a glance

Task: Text Generation
License: apache-2.0
Access: Public
Created: Nov 8, 2024
Updated: Jan 27, 2026
SHA: fdd32982

Try a prompt

Base models

dicta-il/dictalm2.0-instruct

Model card

From the Hugging Face model README

dicta-il/dictalm2.0-instruct - GGUF

This repo contains GGUF format model files for dicta-il/dictalm2.0-instruct.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Our projects

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<s>[INST] {prompt} [/INST]

Model file specification

Filename	Quant type	File Size	Description
dictalm2.0-instruct-Q2_K.gguf	Q2_K	2.538 GB	smallest, significant quality loss - not recommended for most purposes
dictalm2.0-instruct-Q3_K_S.gguf	Q3_K_S	2.953 GB	very small, high quality loss
dictalm2.0-instruct-Q3_K_M.gguf	Q3_K_M	3.283 GB	very small, high quality loss
dictalm2.0-instruct-Q3_K_L.gguf	Q3_K_L	3.565 GB	small, substantial quality loss
dictalm2.0-instruct-Q4_0.gguf	Q4_0	3.833 GB	legacy; small, very high quality loss - prefer using Q3_K_M
dictalm2.0-instruct-Q4_K_S.gguf	Q4_K_S	3.862 GB	small, greater quality loss
dictalm2.0-instruct-Q4_K_M.gguf	Q4_K_M	4.075 GB	medium, balanced quality - recommended
dictalm2.0-instruct-Q5_0.gguf	Q5_0	4.661 GB	legacy; medium, balanced quality - prefer using Q4_K_M
dictalm2.0-instruct-Q5_K_S.gguf	Q5_K_S	4.661 GB	large, low quality loss - recommended
dictalm2.0-instruct-Q5_K_M.gguf	Q5_K_M	4.786 GB	large, very low quality loss - recommended
dictalm2.0-instruct-Q6_K.gguf	Q6_K	5.541 GB	very large, extremely low quality loss
dictalm2.0-instruct-Q8_0.gguf	Q8_0	7.177 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/dictalm2.0-instruct-GGUF --include "dictalm2.0-instruct-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/dictalm2.0-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

Task: Text Generation
License: apache-2.0
Languages: en, he
Created: Nov 8, 2024
Updated: Jan 27, 2026