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

Pandalyst 7B V1.2 AWQ 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 AWQ and how large is it?

Pandalyst 7B V1.2 AWQ 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 AWQ?

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

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

Pandalyst 7B V1.2 AWQ 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 Awq Base model:pipizhao/pandalyst-... Base model:quantized:pipizhao/... Code En Llama Model-index Quantized Region:us Safetensors

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

Pandalyst 7B V1.2 AWQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

data analysis

Applications:

processing data using pandas

Primary Use Cases:

mastering data analysis using pandas

Considerations:

Model designed for processing and analyzing data using the pandas library.

Additional Notes

Open source model with strong generalization capabilities for various data tables.

Supported Languages

en (English)

Training Details

Data Sources:

Context Length:

4096

Model Architecture:

CodeLlama-7b-Python

Input Output

Input Format:

### Instruction: {prompt} ### Response:

Accepted Modalities:

text

Output Format:

text response

Release Notes

Version:

7B-V1.2

Date:

2023/10/15

Notes:

Now supports plotting and is more powerful.

Version:

7B-V1.1

Date:

2023/09/30

Notes:

Trained with CodeLlama-7b-Python, reaching 76.1 exec@1 in PandaTest_V1.0.

LLM Name	Pandalyst 7B V1.2 AWQ
Repository 🤗	https://huggingface.co/TheBloke/Pandalyst-7B-v1.2-AWQ
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	2026-08-01
Maintainer	TheBloke
Model Type	llama
Model Files	3.9 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
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 AWQ 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 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Smaugv0.1 AWQ	195K / 19.3 GB	9	1
Yarn Llama 2 7B 64K AWQ	64K / 3.9 GB	14	0
Calm2 7B Chat AWQ	32K / 4.4 GB	9	1
Llama 2 7B 32K Instruct AWQ	32K / 3.9 GB	3	2
... SWE Llama 7B Updated 4bit AWQ	16K / 3.9 GB	5	0
Tora Code 7B V1.0 AWQ	16K / 3.9 GB	5	0
...eechless Tora Code 7B V1.0 AWQ	16K / 3.9 GB	6	1
CodeLlama 7B Instruct AWQ	16K / 3.9 GB	278	4
Pandalyst 7B V1.1 AWQ	16K / 3.9 GB	11	1
CodeLlama 7B AWQ	16K / 3.9 GB	75	6

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