What are the hardware requirements for Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit?

Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit requires approximately 7.6 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit?

Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit by dbands — VRAM 7.6GB, 4K context

Name: Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit
Author: dbands

Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit is an open-source language model by dbands. Features: 3.8b LLM, VRAM: 7.6GB, Context: 4K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

4bit Autotrain compatible Base model:finetune:unsloth/ph... Base model:unsloth/phi-3-mini-... Conversational En Endpoints compatible Instruct Mistral Quantized Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/dbands/Phi-3-mini-4k-instruct-orca-math-word-problems-200k-model-16bit

Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit Parameters and Internals

Model Type

text-generation-inference, transformers, unsloth, trl, sft, math

Additional Notes

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

LLM Name	Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit
Repository 🤗	https://huggingface.co/dbands/Phi-3-mini-4k-instruct-orca-math-word-problems-200k-model-16bit
Base Model(s)	...hi 3 Mini 4K Instruct Bnb 4bit unsloth/Phi-3-mini-4k-instruct-bnb-4bit
Model Size	3.8b
Required VRAM	7.6 GB
Updated	2024-09-09
Maintainer	dbands
Model Type	mistral
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 2.6 GB: 2-of-2
Supported Languages	en
Quantization Type	4bit
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.40.1
Tokenizer Class	LlamaTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	32064
Torch Data Type	bfloat16

Rank the Phi 3 Mini 4K Instruct Orca Math Word Problems 200K Model 16bit 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 dbands/Phi-3-mini-4k-instruct-orca-math-word-problems-200k-model-16bit.