What are the hardware requirements for Dolly V2 12B Sharded Bf16?

Dolly V2 12B Sharded Bf16 requires approximately 23.8 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 Dolly V2 12B Sharded Bf16 and how large is it?

Dolly V2 12B Sharded Bf16 is developed by diegi97, a model with 12b 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 Dolly V2 12B Sharded Bf16?

Dolly V2 12B Sharded Bf16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Dolly V2 12B Sharded Bf16 by diegi97 — VRAM 23.8GB, 2K context

Name: Dolly V2 12B Sharded Bf16
Author: diegi97

Dolly V2 12B Sharded Bf16 is an open-source language model by diegi97. Features: 12b LLM, VRAM: 23.8GB, Context: 2K, LLM Explorer Score: 0.06.

Endpoints compatible Gpt neox Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/diegi97/dolly-v2-12b-sharded-bf16

Dolly V2 12B Sharded Bf16 Parameters and Internals

Model Type

text generation

Additional Notes

Utilizes sharding to load the model in parts, directly onto the GPU, optimizing memory resource usage.

Training Details

Methodology:

Sharded loading technique to reduce CPU memory requirements.

LLM Name	Dolly V2 12B Sharded Bf16
Repository 🤗	https://huggingface.co/diegi97/dolly-v2-12b-sharded-bf16
Model Size	12b
Required VRAM	23.8 GB
Updated	2026-07-24
Maintainer	diegi97
Model Type	gpt_neox
Model Files	2.0 GB: 1-of-13 1.9 GB: 2-of-13 1.9 GB: 3-of-13 1.9 GB: 4-of-13 1.9 GB: 5-of-13 1.9 GB: 6-of-13 1.9 GB: 7-of-13 1.9 GB: 8-of-13 1.9 GB: 9-of-13 1.9 GB: 10-of-13 1.9 GB: 11-of-13 1.9 GB: 12-of-13 0.9 GB: 13-of-13
Model Architecture	GPTNeoXForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.26.1
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50280
Torch Data Type	bfloat16

Rank the Dolly V2 12B Sharded Bf16 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

Quantized Models of the Dolly V2 12B Sharded Bf16

Model	Likes	Downloads	VRAM
Dolly V2 12B Sharded 8bit	4	5	12 GB

Best Alternatives to Dolly V2 12B Sharded Bf16

Best Alternatives	Context / RAM	Downloads	Likes
Dolly V2 12B	2K / 23.8 GB	3283	1955
...sst Sft 4 Pythia 12B Epoch 3.5	2K / 23.8 GB	818	368
Pythia 12B	2K / 23.8 GB	147000	145
Oasst Rl 1 Pythia 12B	2K / 23.8 GB	10	4
...st Sft 3 Pythia 12B Epoch 2.35	2K / 23.8 GB	10	0
Pythia 12B Deduped	2K / 23.8 GB	4172	53
Oasst Sft 1 Pythia 12B	2K / 23.8 GB	301	277
Pythia 12B Sft V8 7K Steps	2K / 23.8 GB	1106	22
Oasst Pythia 12B Reference	2K / 23.8 GB	1442	0
H2ogpt Oasst1 512 12B	2K / 23.9 GB	242	29

Note: green Score (e.g. "73.2") means that the model is better than diegi97/dolly-v2-12b-sharded-bf16.