What are the hardware requirements for Atomgpt Mistral Tc Supercon?

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

Who developed Atomgpt Mistral Tc Supercon and how large is it?

Atomgpt Mistral Tc Supercon is developed by knc6, 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 Atomgpt Mistral Tc Supercon?

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

Atomgpt Mistral Tc Supercon by knc6 — VRAM 0.2GB

Name: Atomgpt Mistral Tc Supercon
Author: knc6

Atomgpt Mistral Tc Supercon is an open-source language model by knc6. Features: 7b LLM, VRAM: 0.2GB, License: mit, Quantized, LLM Explorer Score: 0.13.

4bit Adapter Atomgpt Base model:adapter:unsloth/mis... Base model:unsloth/mistral-7b-... Chemistry En Finetuned Lora Peft Quantized Region:us Safetensors Superconductors

Model Card on HF 🤗: https://huggingface.co/knc6/atomgpt_mistral_tc_supercon

Atomgpt Mistral Tc Supercon Parameters and Internals

Model Type

text-generation

Additional Notes

Fine-tune models for atomic structure generation of superconductor candidate materials.

Supported Languages

en (proficient)

LLM Name	Atomgpt Mistral Tc Supercon
Repository 🤗	https://huggingface.co/knc6/atomgpt_mistral_tc_supercon
Base Model(s)	Mistral 7B Bnb 4bit unsloth/mistral-7b-bnb-4bit
Model Size	7b
Required VRAM	0.2 GB
Updated	2026-07-19
Maintainer	knc6
Model Files	0.2 GB 0.0 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	Adapter
License	mit
Model Max Length	32768
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	o_proj\|q_proj\|v_proj\|up_proj\|k_proj\|gate_proj\|down_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the Atomgpt Mistral Tc Supercon 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 knc6/atomgpt_mistral_tc_supercon.