What are the hardware requirements for AmhariXLM 0.5B?

AmhariXLM 0.5B requires approximately 2.3 GB of VRAM and supports a context window of 0.2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed AmhariXLM 0.5B and how large is it?

AmhariXLM 0.5B is developed by fidelizML, a model with 0.5b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate AmhariXLM 0.5B?

AmhariXLM 0.5B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

AmhariXLM 0.5B by fidelizML — VRAM 2.3GB, 0.2K context

Name: AmhariXLM 0.5B
Author: fidelizML

AmhariXLM 0.5B is an open-source language model by fidelizML. Features: 0.5b LLM, VRAM: 2.3GB, Context: 0.2K, License: apache-2.0.

Am Amharic Amharixlm Base model:finetune:yisberh/fi... Base model:yisberh/fidel law 1 Chatml Education En Endpoints compatible English Fidelizml Llama Model-index Region:us Safetensors Sft

Model Card on HF 🤗: https://huggingface.co/fidelizML/AmhariXLM-0.5B

AmhariXLM 0.5B Parameters and Internals

LLM Name	AmhariXLM 0.5B
Repository 🤗	https://huggingface.co/fidelizML/AmhariXLM-0.5B
Base Model(s)	Fidel Law 1 yisberh/fidel_law_1
Model Size	0.5b
Required VRAM	2.3 GB
Updated	2026-11-05
Maintainer	fidelizML
Model Type	llama
Model Files	2.3 GB
Supported Languages	am en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	250
Model Max Length	250
Transformers Version	5.20.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	24000

Rank the AmhariXLM 0.5B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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Note: green Score (e.g. "73.2") means that the model is better than fidelizML/AmhariXLM-0.5B.