What are the hardware requirements for Llama 31 Hhrlhf Squad Rlhf Policy Model?

Llama 31 Hhrlhf Squad Rlhf Policy Model requires approximately 2.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 31 Hhrlhf Squad Rlhf Policy Model and how large is it?

Llama 31 Hhrlhf Squad Rlhf Policy Model is developed by almorin, a model with 1b 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 Llama 31 Hhrlhf Squad Rlhf Policy Model?

Llama 31 Hhrlhf Squad Rlhf Policy Model is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 31 Hhrlhf Squad Rlhf Policy Model by almorin — VRAM 2.5GB, 128K context

Name: Llama 31 Hhrlhf Squad Rlhf Policy Model
Author: almorin

Llama 31 Hhrlhf Squad Rlhf Policy Model is an open-source language model by almorin. Features: 1b LLM, VRAM: 2.5GB, Context: 128K, Instruction-Based, LLM Explorer Score: 0.18.

Arxiv:1910.09700 Autotrain compatible Conversational Endpoints compatible Instruct Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/almorin/llama-31-hhrlhf-squad-rlhf-policy-model

Llama 31 Hhrlhf Squad Rlhf Policy Model Parameters and Internals

LLM Name	Llama 31 Hhrlhf Squad Rlhf Policy Model
Repository 🤗	https://huggingface.co/almorin/llama-31-hhrlhf-squad-rlhf-policy-model
Model Size	1b
Required VRAM	2.5 GB
Updated	2025-09-23
Maintainer	almorin
Model Type	llama
Instruction-Based	Yes
Model Files	2.5 GB
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.44.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
Vocabulary Size	128256
Torch Data Type	float16

Rank the Llama 31 Hhrlhf Squad Rlhf Policy Model 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 almorin/llama-31-hhrlhf-squad-rlhf-policy-model.