What are the hardware requirements for PyJamba1B?

PyJamba1B requires approximately 2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed PyJamba1B and how large is it?

PyJamba1B is developed by isemmanuelolowe, a model with 1b 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 PyJamba1B?

PyJamba1B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

PyJamba1B by isemmanuelolowe — VRAM 2GB

Name: PyJamba1B
Author: isemmanuelolowe

PyJamba1B is an open-source language model by isemmanuelolowe. Features: 1b LLM, VRAM: 2GB, License: mit, LLM Explorer Score: 0.12.

Custom code Endpoints compatible Jamba Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/isemmanuelolowe/PyJamba1B

PyJamba1B Parameters and Internals

Additional Notes

Model is currently in training and is incoherent.

LLM Name	PyJamba1B
Repository 🤗	https://huggingface.co/isemmanuelolowe/PyJamba1B
Model Size	1b
Required VRAM	2 GB
Updated	2026-07-30
Maintainer	isemmanuelolowe
Model Type	jamba
Model Files	2.0 GB 0.0 GB
Model Architecture	JambaForCausalLM
License	mit
Transformers Version	4.40.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	<\|pad\|>
Vocabulary Size	65536
Torch Data Type	bfloat16

Rank the PyJamba1B 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 PyJamba1B

Best Alternatives	Context / RAM	Downloads	Likes
...H1024 L12 V0.07 Fineweb 1M Med	16K / 1.8 GB	9	0
...amba UltraInteract Instruct 1B	0K / 4.1 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than isemmanuelolowe/PyJamba1B.