What are the hardware requirements for Phi 1 5 Tldr Sft?

Phi 1 5 Tldr Sft requires approximately 5.7 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Phi 1 5 Tldr Sft and how large is it?

Phi 1 5 Tldr Sft is developed by aklein4, a model with 1.4b 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 Phi 1 5 Tldr Sft?

Phi 1 5 Tldr Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Phi 1 5 Tldr Sft by aklein4 — VRAM 5.7GB, 2K context

Name: Phi 1 5 Tldr Sft
Author: aklein4

Phi 1 5 Tldr Sft is an open-source language model by aklein4. Features: 1.4b LLM, VRAM: 5.7GB, Context: 2K, LLM Explorer Score: 0.13.

Arxiv:1910.09700 Autotrain compatible Endpoints compatible Phi Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/aklein4/phi-1_5-tldr-sft

Phi 1 5 Tldr Sft Parameters and Internals

LLM Name	Phi 1 5 Tldr Sft
Repository 🤗	https://huggingface.co/aklein4/phi-1_5-tldr-sft
Model Size	1.4b
Required VRAM	5.7 GB
Updated	2025-09-21
Maintainer	aklein4
Model Type	phi
Model Files	5.0 GB: 1-of-2 0.7 GB: 2-of-2
Model Architecture	PhiForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.41.2
Vocabulary Size	51200
Torch Data Type	float32

Rank the Phi 1 5 Tldr Sft capabilities

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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 aklein4/phi-1_5-tldr-sft.