What are the hardware requirements for User23ContinuedFine?

User23ContinuedFine requires approximately 14.5 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed User23ContinuedFine and how large is it?

User23ContinuedFine is developed by AlSamCur123, 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 User23ContinuedFine?

User23ContinuedFine is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

User23ContinuedFine by AlSamCur123 — VRAM 14.5GB, 32K context

Name: User23ContinuedFine
Author: AlSamCur123

User23ContinuedFine is an open-source language model by AlSamCur123. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.15.

4bit Autotrain compatible Base model:finetune:unsloth/mi... Base model:unsloth/mistral-7b-... En Endpoints compatible Mistral Quantized Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/AlSamCur123/User23ContinuedFine

User23ContinuedFine Parameters and Internals

LLM Name	User23ContinuedFine
Repository 🤗	https://huggingface.co/AlSamCur123/User23ContinuedFine
Base Model(s)	unsloth/mistral-7b-v0.3-bnb-4bit unsloth/mistral-7b-v0.3-bnb-4bit
Model Size	7b
Required VRAM	14.5 GB
Updated	2025-04-03
Maintainer	AlSamCur123
Model Type	mistral
Model Files	5.0 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Quantization Type	4bit
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.3
Tokenizer Class	LlamaTokenizer
Padding Token	[control_768]
Vocabulary Size	32768
Torch Data Type	float16

Rank the User23ContinuedFine 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 User23ContinuedFine

Best Alternatives	Context / RAM	Downloads	Likes
...t 3.5 0106 128K 4.0bpw H6 EXL2	128K / 3.9 GB	4	1
...t 3.5 0106 128K 8.0bpw H8 EXL2	128K / 7.4 GB	1	1
...aude Sonnet Mistral 7B It V0.3	32K / 14.5 GB	7	2
Mistral 7B V0.3 Bnb 4bit	32K / 4.1 GB	381323	22
Mistral 7B Instruct V0.2 Fp16	32K / 14.4 GB	26	0
Mistral 7B Instruct V0.2 4bit	32K / 4.3 GB	79	1
...tral 7B Instruct V0.3 Bnb 4bit	32K / 4.1 GB	34633	42
Mistral 7B Instruct V0.2 8bit	32K / 7.6 GB	5	1
...tral 7B Instruct V0.2 Bnb 4bit	32K / 4.1 GB	7160	35
Mixtral V0.3 Full 16bit	32K / 14.5 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than AlSamCur123/User23ContinuedFine.