What are the hardware requirements for OpenBezoar HH RLHF SFT?

OpenBezoar HH RLHF SFT requires approximately 6.8 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed OpenBezoar HH RLHF SFT and how large is it?

OpenBezoar HH RLHF SFT is developed by SurgeGlobal, a model with 3b 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 OpenBezoar HH RLHF SFT?

OpenBezoar HH RLHF SFT is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

OpenBezoar HH RLHF SFT by SurgeGlobal — VRAM 6.8GB, 2K context

Name: OpenBezoar HH RLHF SFT
Author: SurgeGlobal

OpenBezoar HH RLHF SFT is an open-source language model by SurgeGlobal. Features: 3b LLM, VRAM: 6.8GB, Context: 2K, License: cc-by-nc-4.0, LLM Explorer Score: 0.09.

Arxiv:2306.02707 Arxiv:2404.12195 Base model:finetune:surgegloba... Base model:surgeglobal/openbez... Dataset:anthropic/hh-rlhf En Endpoints compatible Llama Pytorch Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/SurgeGlobal/OpenBezoar-HH-RLHF-SFT

OpenBezoar HH RLHF SFT Parameters and Internals

Model Type

text generation

Use Cases

Limitations:

The model might not consistently show improved abilities to follow instructions, and it could respond inappropriately or get stuck in loops., This model is not aligned to human preferences and therefore it may generate harmful and uncensored content., Caution is urged against relying on this model for production or adjacent use-cases.

Supported Languages

en ()

Training Details

Data Sources:

Anthropic HH-RLHF Dataset

Data Volume:

First 100K examples

Methodology:

Supervised Fine-Tuning (SFT)

Model Architecture:

OpenLLaMA 3B v2

Input Output

Input Format:

Alpaca prompt template

Performance Tips:

It is important to utilize the Alpaca prompt template in order to obtain best responses for instruction related tasks.

LLM Name	OpenBezoar HH RLHF SFT
Repository 🤗	https://huggingface.co/SurgeGlobal/OpenBezoar-HH-RLHF-SFT
Base Model(s)	OpenBezoar SFT SurgeGlobal/OpenBezoar-SFT
Model Size	3b
Required VRAM	6.8 GB
Updated	2026-07-24
Maintainer	SurgeGlobal
Model Type	llama
Model Files	6.8 GB 6.8 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	cc-by-nc-4.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.33.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the OpenBezoar HH RLHF SFT 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 SurgeGlobal/OpenBezoar-HH-RLHF-SFT.