What are the hardware requirements for Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged?

Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged requires approximately 14.4 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.

Where can I download or evaluate Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged?

Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged by Ayush-1722 — VRAM 14.4GB, 128K context

Name: Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged
Author: Ayush-1722

Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged is an open-source language model by Ayush-1722. Features: 7b LLM, VRAM: 14.4GB, Context: 128K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.12.

Arxiv:2310.06825 Big patents 200k+ context length 7b Chat Conversational Dataset:facebook/babi qa Dataset:rmt-team/babilong Dataset:rmt-team/babilong-1k-s... Dataset:trelis/big patent 100k... Endpoints compatible Finetuned Instruct Long context Lora Mistral Norm & embed trained Question answering Region:us Research Rope Safetensors Science Sharded Summarize Tensorflow Theta scaling

Model Card on HF 🤗: https://huggingface.co/Ayush-1722/Mistral-7B-Instruct-v0.1-Summarize-64K-LoRANET-Merged

Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged Parameters and Internals

Model Type

text-generation, summarize, instruct, question-answering, chat, conversational, research, science

Additional Notes

The model does not have any moderation mechanisms and discussions with the community are awaited to incorporate guardrails into the deployment environment.

Training Details

Data Sources:

RMT-team/babilong, RMT-team/babilong-1k-samples, Trelis/big_patent_100k_characters, facebook/babi_qa

Methodology:

Instruction fine-tuning with conversation datasets

Model Architecture:

Mistral-7B-v0.1 based transformer with Grouped-Query Attention and Sliding-Window Attention

Input Output

Input Format:

Surround your prompt with `[INST]` and `[/INST]` tokens.

LLM Name	Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged
Repository 🤗	https://huggingface.co/Ayush-1722/Mistral-7B-Instruct-v0.1-Summarize-64K-LoRANET-Merged
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-09-07
Maintainer	Ayush-1722
Model Type	mistral
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.40.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged 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 Mistral 7B Instruct V0.1 Summarize 64K LoRANET Merged

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
... Summarize 64K QLoRANET Merged	128K / 4.1 GB	11	0
Mistral 7B Instruct V0.2	32K / 14.4 GB	1115337	3184
Mistral 7B Instruct V0.1	32K / 14.4 GB	253629	1846
Mistral 7B Instruct V0.2	32K / 14.4 GB	1338	0
Copywriting Llm	32K / 4.1 GB	122	1
Mixtral AI CyberCoder	32K / 14.3 GB	0	0

Note: green Score (e.g. "73.2") means that the model is better than Ayush-1722/Mistral-7B-Instruct-v0.1-Summarize-64K-LoRANET-Merged.