What are the hardware requirements for Huozi 7B Rlhf?

Huozi 7B Rlhf requires approximately 15.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Huozi 7B Rlhf and how large is it?

Huozi 7B Rlhf is developed by HIT-SCIR, 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 Huozi 7B Rlhf?

Huozi 7B Rlhf is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Huozi 7B Rlhf by HIT-SCIR — VRAM 15.6GB

Name: Huozi 7B Rlhf
Author: HIT-SCIR

Huozi 7B Rlhf is an open-source language model by HIT-SCIR. Features: 7b LLM, VRAM: 15.6GB, LLM Explorer Score: 0.08.

Bloom Endpoints compatible Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/HIT-SCIR/huozi-7b-rlhf

Huozi 7B Rlhf Parameters and Internals

LLM Name	Huozi 7B Rlhf
Repository 🤗	https://huggingface.co/HIT-SCIR/huozi-7b-rlhf
Model Size	7b
Required VRAM	15.6 GB
Updated	2026-07-13
Maintainer	HIT-SCIR
Model Type	bloom
Model Files	0.0 GB: 1-of-16 2.0 GB: 2-of-16 0.9 GB: 3-of-16 0.9 GB: 4-of-16 0.9 GB: 5-of-16 0.9 GB: 6-of-16 0.9 GB: 7-of-16 0.9 GB: 8-of-16 0.9 GB: 9-of-16 0.9 GB: 10-of-16 0.9 GB: 11-of-16 0.9 GB: 12-of-16 0.9 GB: 13-of-16 0.9 GB: 14-of-16 0.8 GB: 15-of-16 2.0 GB: 16-of-16
Model Architecture	BloomForCausalLM
Transformers Version	4.28.1
Tokenizer Class	BloomTokenizer
Padding Token	<pad>
Vocabulary Size	250688
Torch Data Type	float16

Rank the Huozi 7B Rlhf 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 HIT-SCIR/huozi-7b-rlhf.