What are the hardware requirements for Vigogne Bloom 7b1 Instruct?

Vigogne Bloom 7b1 Instruct requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Vigogne Bloom 7b1 Instruct and how large is it?

Vigogne Bloom 7b1 Instruct is developed by bofenghuang. 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 Vigogne Bloom 7b1 Instruct?

Vigogne Bloom 7b1 Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Vigogne Bloom 7b1 Instruct by bofenghuang — VRAM 0.1GB

Name: Vigogne Bloom 7b1 Instruct
Author: bofenghuang

Vigogne Bloom 7b1 Instruct is an open-source language model by bofenghuang. Features: LLM, VRAM: 0.1GB, License: bigscience-bloom-rail-1.0, Instruction-Based, LLM Explorer Score: 0.06.

Alpaca Bloom Dataset:tatsu-lab/alpaca Fr Instruct Lora Region:us Tensorboard

Model Card on HF 🤗: https://huggingface.co/bofenghuang/vigogne-bloom-7b1-instruct

Vigogne Bloom 7b1 Instruct Parameters and Internals

Model Type

text-generation

Use Cases

Limitations:

Model may generate harmful or biased content, Incorrect information, Generally unhelpful answers

Additional Notes

The repo contains only a low-rank adapter. Complete model requires loading base LLM and tokenizer.

Supported Languages

fr (instruction-following)

Training Details

Data Sources:

tatsu-lab/alpaca

Methodology:

fine-tuning on French instructions

LLM Name	Vigogne Bloom 7b1 Instruct
Repository 🤗	https://huggingface.co/bofenghuang/vigogne-bloom-7b1-instruct
Required VRAM	0.1 GB
Updated	2026-08-08
Maintainer	bofenghuang
Instruction-Based	Yes
Model Files	0.1 GB
Supported Languages	fr
Model Architecture	AutoModel
License	bigscience-bloom-rail-1.0
Is Biased	none
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	query_key_value\|dense\|dense_h_to_4h\|dense_4h_to_h
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16

Rank the Vigogne Bloom 7b1 Instruct 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 Vigogne Bloom 7b1 Instruct

Best Alternatives	Context / RAM	Downloads	Likes
...l 8x7B Instruct V0.1 Llamafile	0K / GB	7076	18
Autotrain Umberto Proclama	0K / 0.9 GB	5	0
Mamba Python	0K / 2 GB	13	0
...l 8x7B Instruct V0.1 Llamafile	0K / GB	3180	18
...hi 3 Mini 4K Instruct Ct2 Int8	0K / 3.8 GB	8	1
CSUMLM	0K / GB	13	1
...hin 2.5 Mixtral 8x7b Llamafile	0K / GB	117	4
Instruct GPT J	0K / 0 GB	0	26
...a Instruction Fine Tune French	0K / 0 GB	0	4
MiniMaid L3	0K / 0 GB	9	2

Note: green Score (e.g. "73.2") means that the model is better than bofenghuang/vigogne-bloom-7b1-instruct.