What are the hardware requirements for Granite 34B Code Base?

Granite 34B Code Base requires approximately 67.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Granite 34B Code Base and how large is it?

Granite 34B Code Base is developed by ibm-granite, a model with 34b 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 Granite 34B Code Base?

Granite 34B Code Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Granite 34B Code Base by ibm-granite — VRAM 67.1GB

Name: Granite 34B Code Base
Author: ibm-granite

Granite 34B Code Base is an open-source language model by ibm-granite. Features: 34b LLM, VRAM: 67.1GB, License: apache-2.0, Code Generating, LLM Explorer Score: 0.13.

Arxiv:2405.04324 Autotrain compatible Code Codegen Dataset:bigcode/starcoderdata Dataset:codeparrot/github-code... Dataset:math-ai/stackmathqa Dataset:open-web-math/open-web... Endpoints compatible Gpt bigcode Granite Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ibm-granite/granite-34b-code-base

Granite 34B Code Base Benchmarks

LLME Score: 0.13446

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Granite 34B Code Base (ibm-granite/granite-34b-code-base)

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Granite 34B Code Base Parameters and Internals

LLM Name	Granite 34B Code Base
Repository 🤗	https://huggingface.co/ibm-granite/granite-34b-code-base
Model Size	34b
Required VRAM	67.1 GB
Updated	2024-09-01
Maintainer	ibm-granite
Model Type	gpt_bigcode
Model Files	5.0 GB: 1-of-14 4.9 GB: 2-of-14 4.9 GB: 3-of-14 4.9 GB: 4-of-14 4.9 GB: 5-of-14 4.9 GB: 6-of-14 4.9 GB: 7-of-14 4.9 GB: 8-of-14 4.9 GB: 9-of-14 4.9 GB: 10-of-14 4.9 GB: 11-of-14 4.9 GB: 12-of-14 4.9 GB: 13-of-14 3.3 GB: 14-of-14
Generates Code	Yes
Model Architecture	GPTBigCodeForCausalLM
License	apache-2.0
Model Max Length	8192
Transformers Version	4.38.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	49152
Torch Data Type	bfloat16
Activation Function	gelu_pytorch_tanh

Quantized Models of the Granite 34B Code Base

Model	Likes	Downloads	VRAM
Granite 34B Code Base 4bit	1	48	18 GB

Best Alternatives to Granite 34B Code Base

Best Alternatives	Context / RAM	Downloads	Likes
Granite 34B Code Instruct 8K	0K / 67.1 GB	100014	78
Granite 34B Code Instruct	0K / 67.1 GB	2710	68
Granite 34B Code Base 8K	0K / 67.1 GB	501	20
Granite 34B Code Base 4bit	0K / 18.9 GB	48	1
Granite 34B Code Instruct AWQ	0K / 18.6 GB	64	3

Note: green Score (e.g. "73.2") means that the model is better than ibm-granite/granite-34b-code-base.

Rank the Granite 34B Code Base Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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

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Granite 34B Code Base by ibm-granite