What are the hardware requirements for Mistralbasket1?

Mistralbasket1 requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistralbasket1 and how large is it?

Mistralbasket1 is developed by samirun974, 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 Mistralbasket1?

Mistralbasket1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistralbasket1 by samirun974 — VRAM 0.2GB

Name: Mistralbasket1
Author: samirun974

Mistralbasket1 is an open-source language model by samirun974. Features: 7b LLM, VRAM: 0.2GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.12.

4-bit 4bit Base model:quantized:unsloth/m... Base model:unsloth/mistral-7b-... Bitsandbytes Conversational Endpoints compatible Fr Lora Mistral Quantized Region:us Safetensors Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/samirun974/mistralbasket1

Mistralbasket1 Parameters and Internals

Model Type

text-generation-inference, transformers

Additional Notes

This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.

LLM Name	Mistralbasket1
Repository 🤗	https://huggingface.co/samirun974/mistralbasket1
Base Model(s)	unsloth/mistral-7b-v0.2-bnb-4bit unsloth/mistral-7b-v0.2-bnb-4bit
Model Size	7b
Required VRAM	0.2 GB
Updated	2026-07-31
Maintainer	samirun974
Model Files	0.2 GB 4.1 GB
Supported Languages	fr
Quantization Type	4bit
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Model Max Length	32768
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|v_proj\|o_proj\|up_proj\|gate_proj\|k_proj\|down_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the Mistralbasket1 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 Mistralbasket1

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 8K Sports	0K / 15.2 GB	14	0
WorldBuilder 7B	0K / 14.5 GB	4	1
Unsloth Alpaca	0K / 14.5 GB	5	0
... WAEMU Africa Banking Analysis	0K / 15.2 GB	6	1
Gemma 7B Bnb 4bit	0K / 17.1 GB	5	0
Mistral 7B V0.3	0K / 14.5 GB	5	0
Refined Llama3	0K / 0.2 GB	6	0
Unsloth Vinallama	0K / 14.4 GB	22	0
Gemma Unsloth Alpaca	0K / 17.1 GB	5	2
Mistral 7B Instruct 4bit	0K / 0.2 GB	11	1

Note: green Score (e.g. "73.2") means that the model is better than samirun974/mistralbasket1.