Model Details
Full Model IDuzlm/alloma-3B-Instruct
Pipeline / Tasktext-generation
Librarytransformers
Downloads (all-time)54.8K
Likes6
Last Modified9/30/2025
Author / Orguzlm
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-generation", model="uzlm/alloma-3B-Instruct")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsllamatext-generationuzbekuzbekllmuzbeknlptranslationsummarizationquestion-answeringtokenizerconversationaluzendataset:HuggingFaceFW/fineweb-2dataset:tahrirchi/uz-crawldataset:yakhyo/uz-wikidataset:wikipediadataset:tatsu-lab/alpacadataset:behbudiy/alpaca-cleaned-uzdataset:UAzimov/uzbek-instruct-llmdataset:behbudiy/translation-instructionbase_model:meta-llama/Llama-3.2-3B-Instructbase_model:finetune:meta-llama/Llama-3.2-3B-Instructlicense:llama3.2text-generation-inferenceendpoints_compatibleregion:us
More Text Generation Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models✍️ Task: Text Generation
This model is designed for the Text Generation task. Explore more models for this use case.
All Text Generation Models →📊 Popularity
⬇ Downloads54.8K
❤️ Community Likes6
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.