What are the hardware requirements for Followup V6?

Followup V6 requires approximately 7.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Followup V6 and how large is it?

Followup V6 is developed by shubhamrathore081, a model with 3.8b 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 Followup V6?

Followup V6 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Followup V6 by shubhamrathore081 — VRAM 7.6GB

Name: Followup V6
Author: shubhamrathore081

Followup V6 is an open-source language model by shubhamrathore081. Features: 3.8b LLM, VRAM: 7.6GB, License: apache-2.0, Instruction-Based.

Autotrain compatible Base model:unsloth/phi-3-mini-... Conversational En Endpoints compatible Instruct License:apache-2.0 Lora Mistral Region:us Safetensors Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/shubhamrathore081/followup_v6

Followup V6 Parameters and Internals

LLM Name	Followup V6
Repository 🤗	https://huggingface.co/shubhamrathore081/followup_v6
Base Model(s)	Phi 3 Mini 4K Instruct unsloth/Phi-3-mini-4k-instruct
Model Size	3.8b
Required VRAM	7.6 GB
Updated	2024-07-04
Maintainer	shubhamrathore081
Instruction-Based	Yes
Model Files	0.2 GB 5.0 GB: 1-of-2 2.6 GB: 2-of-2
Supported Languages	en
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Model Max Length	4096
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<\|placeholder6\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|o_proj\|down_proj\|v_proj\|gate_proj\|k_proj\|up_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	32

Rank the Followup V6 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 Followup V6

Best Alternatives	Context / RAM	Downloads	Likes
Kittylm Phi 4 Mini	0K / 0.1 GB	244	0
Phi 3 Mini Instruct 16bit	0K / 7.6 GB	6	0
...ct Bnb 4bit 16 4 100 1 Nonmath	0K / 7.6 GB	86	1

Note: green Score (e.g. "73.2") means that the model is better than shubhamrathore081/followup_v6.