What are the hardware requirements for X Instruction 7B 10langs?

X Instruction 7B 10langs requires approximately 17.1 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed X Instruction 7B 10langs and how large is it?

X Instruction 7B 10langs is developed by James-WYang, a model with 7b 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 X Instruction 7B 10langs?

X Instruction 7B 10langs is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

X Instruction 7B 10langs by James-WYang — VRAM 17.1GB, 8K context

Name: X Instruction 7B 10langs
Author: James-WYang

X Instruction 7B 10langs is an open-source language model by James-WYang. Features: 7b LLM, VRAM: 17.1GB, Context: 8K, License: mit, Instruction-Based, LLM Explorer Score: 0.12.

Endpoints compatible Gemma Instruct Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/James-WYang/X-Instruction-7b-10langs

X Instruction 7B 10langs Parameters and Internals

LLM Name	X Instruction 7B 10langs
Repository 🤗	https://huggingface.co/James-WYang/X-Instruction-7b-10langs
Model Size	7b
Required VRAM	17.1 GB
Updated	2026-08-01
Maintainer	James-WYang
Model Type	gemma
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 5.0 GB: 3-of-4 2.1 GB: 4-of-4
Model Architecture	GemmaForCausalLM
License	mit
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the X Instruction 7B 10langs 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 James-WYang/X-Instruction-7b-10langs.