What are the hardware requirements for PARM 1 Smollm2 1.7B Lcot PyTorch?

PARM 1 Smollm2 1.7B Lcot PyTorch requires approximately 3.4 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed PARM 1 Smollm2 1.7B Lcot PyTorch and how large is it?

PARM 1 Smollm2 1.7B Lcot PyTorch is developed by Pinkstack, a model with 1.7b 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 PARM 1 Smollm2 1.7B Lcot PyTorch?

PARM 1 Smollm2 1.7B Lcot PyTorch is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

PARM 1 Smollm2 1.7B Lcot PyTorch by Pinkstack — VRAM 3.4GB, 8K context

Name: PARM 1 Smollm2 1.7B Lcot PyTorch
Author: Pinkstack

PARM 1 Smollm2 1.7B Lcot PyTorch is an open-source language model by Pinkstack. Features: 1.7b LLM, VRAM: 3.4GB, Context: 8K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.16.

Base model:finetune:huggingfac... Base model:huggingfacetb/smoll... Conversational En Endpoints compatible Instruct Llama Pytorch Region:us Safetensors Sft Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/Pinkstack/PARM-1-Smollm2-1.7B-Lcot-PyTorch

PARM 1 Smollm2 1.7B Lcot PyTorch Parameters and Internals

LLM Name	PARM 1 Smollm2 1.7B Lcot PyTorch
Repository 🤗	https://huggingface.co/Pinkstack/PARM-1-Smollm2-1.7B-Lcot-PyTorch
Base Model(s)	HuggingFaceTB/SmolLM2-1.7B-Instruct HuggingFaceTB/SmolLM2-1.7B-Instruct
Model Size	1.7b
Required VRAM	3.4 GB
Updated	2026-07-01
Maintainer	Pinkstack
Model Type	llama
Instruction-Based	Yes
Model Files	3.4 GB 3.4 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.47.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	49153
Torch Data Type	float16

Rank the PARM 1 Smollm2 1.7B Lcot PyTorch 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 PARM 1 Smollm2 1.7B Lcot PyTorch

Best Alternatives	Context / RAM	Downloads	Likes
SmolLM2 1.7B Instruct 16K	16K / 3.4 GB	103	10
SmolLM2 1.7B Instruct	8K / 3.4 GB	154013	742
Yoru	8K / 3.4 GB	309	0
SmolLM2 1.7B Instruct	8K / 3.4 GB	4909	6
...ygnis Alpha 1.7B V0.1 Instruct	8K / 3.4 GB	11	2
SmolTulu 1.7B Reinforced	8K / 3.4 GB	12	5
SmolLM2 1.7 Persona	8K / 3.5 GB	7	0
Superthoughts Lite V1	8K / 3.4 GB	92	3
Penny 1.7B	8K / 6.9 GB	18	24
...ghts Lite 1.8B Experimental O1	8K / 3.6 GB	11	2

Note: green Score (e.g. "73.2") means that the model is better than Pinkstack/PARM-1-Smollm2-1.7B-Lcot-PyTorch.