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CodeLLaMA-34B

Coding modelCodeLlama

CodeLLaMA-34B

Release date: 2023-08-24Updated: 2023-08-24Views: 556
Live demoGitHubHugging FaceCompare
Parameters
34B
Context length
100K
Multilingual
No data
Reasoning ability
No data

CodeLLaMA-34B is an AI model published by Facebook AI Research Lab, released on 2023-08-24, for Coding model, with 34B parameters, and 100K context length, requiring about 68GB storage, with a 93.00 score on HumanEval.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

CodeLLaMA-34B

Model basics

Reasoning traces
No data
Thinking modes
Thinking modes not supported
Context length
100K tokens
Max output length
No data
Model type
Coding model
Modality (in / out)
No data
Release date
2023-08-24
Model file size
68GB
MoE architecture
No
Total params / Active params
34B / Not applicable
Knowledge cutoff
No data
CodeLLaMA-34B

Open source & experience

Code license
Weights license
- Commercial use permitted
Hugging Face
N/A
Live demo
N/A
CodeLLaMA-34B

Official resources

Paper
DataLearnerAI blog
N/A
CodeLLaMA-34B

API details

API speed
No data
No public API pricing yet.
CodeLLaMA-34B

Benchmark Results

CodeLLaMA-34B currently shows benchmark results led by HumanEval (7 / 140, score 93), MBPP (8 / 96, score 86.60). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.

Thinking

Coding and Software Engineer

6 evaluations
Benchmark / mode
Score
Rank/total
HumanEval
Standard Mode
93
7 / 140
HumanEval
Standard Mode
76.80
46 / 140
HumanEval
Standard Mode
48.80
85 / 140
MBPP
Standard Mode
86.60
8 / 96
MBPP
Standard Mode
76.20
26 / 96
MBPP
Standard Mode
55
58 / 96
CodeLLaMA-34B

Publisher

Facebook AI Research Lab
Facebook AI Research Lab
View publisher details
CodeLLaMA-34B

Model Overview

CodeLLaMA-34B is an AI model published by Facebook AI Research Lab, released on 2023-08-24, for Coding model, with 34B parameters, and 100K context length, requiring about 68GB storage, with a 93.00 score on HumanEval.

Foundation model

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