What are the hardware requirements for Pandalyst 7B V1.2 GPTQ?

Pandalyst 7B V1.2 GPTQ requires approximately 3.9 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Pandalyst 7B V1.2 GPTQ and how large is it?

Pandalyst 7B V1.2 GPTQ is developed by TheBloke, a model with 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 Pandalyst 7B V1.2 GPTQ?

Pandalyst 7B V1.2 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Pandalyst 7B V1.2 GPTQ by TheBloke — VRAM 3.9GB, 16K context

Name: Pandalyst 7B V1.2 GPTQ
Author: TheBloke

Pandalyst 7B V1.2 GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 16K, License: llama2, Quantized, LLM Explorer Score: 0.09.

4-bit Base model:pipizhao/pandalyst-... Base model:quantized:pipizhao/... Code En Gptq Llama Model-index Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Pandalyst-7B-v1.2-GPTQ

Pandalyst 7B V1.2 GPTQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

data analysis

Applications:

using pandas library, handling complex data tables

Additional Notes

Pandalyst is designed for mastering data analysis using the pandas library. It is open source and free for use.

Supported Languages

en (high proficiency)

Training Details

Data Sources:

CodeLlama-7b-Python

Context Length:

4096

Input Output

Input Format:

Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {prompt} ### Response:

Accepted Modalities:

text

Output Format:

text

Release Notes

Version:

7B V1.2

Date:

2023/10/15

Notes:

Supports plotting and surpasses previous versions and ChatGPT-3.5 in performance.

Version:

7B V1.1

Date:

2023/09/30

Notes:

Achieves 76.1 exec@1 in PandaTest_V1.0.

LLM Name	Pandalyst 7B V1.2 GPTQ
Repository 🤗	https://huggingface.co/TheBloke/Pandalyst-7B-v1.2-GPTQ
Model Name	Pandalyst 7B v1.2
Model Creator	pipizhao
Base Model(s)	pipizhao/Pandalyst-7B-V1.2 pipizhao/Pandalyst-7B-V1.2
Model Size	7b
Required VRAM	3.9 GB
Updated	2026-07-06
Maintainer	TheBloke
Model Type	llama
Model Files	3.9 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.34.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32001
Torch Data Type	float16

Rank the Pandalyst 7B V1.2 GPTQ 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 Pandalyst 7B V1.2 GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Yarn Llama 2 7B 128K GPTQ	128K / 3.9 GB	8	7
Yarn Llama 2 7B 64K GPTQ	64K / 3.9 GB	10	1
... 7B 32K Instructions V4 Marlin	32K / 4.1 GB	8	0
Aixcoder 7B GPTQ	32K / 4.5 GB	4	1
Calm2 7B Chat GPTQ	32K / 4.4 GB	6	5
...Calm2 7B Chat GPTQ Calib Ja 1K	32K / 4.4 GB	4	5
Llama 2 7B 32K Instruct GPTQ	32K / 3.9 GB	49	27
Codebear 7B 4bit	16K / 3.9 GB	4	1
...a 7B Instruct GPTQ Calib Ja 1K	16K / 3.9 GB	6	0
Tora Code 7B V1.0 GPTQ	16K / 3.9 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Pandalyst-7B-v1.2-GPTQ.