What are the hardware requirements for Model?

Model requires approximately 7.6 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 Model and how large is it?

Model is developed by abanm, a model with 3.8b 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 Model?

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

Model by abanm — VRAM 7.6GB, 128K context

Name: Model
Author: abanm

Model is an open-source language model by abanm. Features: 3.8b LLM, VRAM: 7.6GB, Context: 128K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.16.

4bit Autotrain compatible Conversational En Endpoints compatible Instruct Llama Quantized Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/abanm/model

Model Parameters and Internals

LLM Name	Model
Repository 🤗	https://huggingface.co/abanm/model
Base Model(s)	unsloth/phi-3.5-mini-instruct-bnb-4bit unsloth/phi-3.5-mini-instruct-bnb-4bit
Model Size	3.8b
Required VRAM	7.6 GB
Updated	2025-01-21
Maintainer	abanm
Model Type	llama
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 2.6 GB: 2-of-2
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.47.1
Tokenizer Class	LlamaTokenizer
Padding Token	<\|placeholder6\|>
Vocabulary Size	32064
Torch Data Type	bfloat16

Rank the 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

Best Alternatives to Model

Best Alternatives	Context / RAM	Downloads	Likes
Legal Chatbot Qlora Id	128K / 7.6 GB	69	0
Phi 3.5 Indo Legal Exp2	128K / 7.6 GB	21	0
DeepPhi 3.5 Mini Instruct	128K / 7.6 GB	5	0
Phi 3 5 Mini 3k Each	128K / 7.6 GB	5	0
...ene Phi 3.5 Mini Instruct Orpo	128K / 7.6 GB	9	2
Tara 3.8B	146K / 7.6 GB	10	0
...hi3 Unlearning General Methode	128K / 7.6 GB	355	0
Superthoughts Mini V1.3.8B	128K / 7.6 GB	78	1
Phi 3.5 Mini Instruct	128K / 7.6 GB	3544	50
Phi 3 5 Mini Kp 12k Cfr Sft	128K / 7.6 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than abanm/model.