DeepSeek Coder V2 Lite Instruct By deepseek-ai: Benchmarks, Features and Detailed Analysis. Insights on DeepSeek Coder V2 Lite Instruct.

Arxiv:2401.06066 Autotrain compatible Codegen Conversational Custom code Deepseek v2 Endpoints compatible Instruct Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct

DeepSeek Coder V2 Lite Instruct Benchmarks

LLME Score: 0.35279

^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)

DeepSeek Coder V2 Lite Instruct (deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct)

DeepSeek Coder V2 Lite Instruct Parameters and Internals

Model Type

Mixture-of-Experts (MoE), code language model

Use Cases

Areas:

code-specific tasks, math and reasoning, programming languages extension

Applications:

AI code assistance, software development, research in code intelligence

Primary Use Cases:

Code completion, Code insertion, Chatbot assistance for coding queries

Limitations:

Optimal performance requires specified hardware, Compatibility with certain APIs necessary

Additional Notes

Supported languages expanded to 338 from 86. Allows for commercial use.

Supported Languages

languages_supported (, programming languages: 338, extended from 86), competence_level (high proficiency in code-specific tasks)

Training Details

Data Sources:

DeepSeekMoE framework, intermediate checkpoint of DeepSeek-V2, additional 6 trillion tokens

Data Volume:

6 trillion tokens

Methodology:

Mixture-of-experts mechanism for enhanced coding and reasoning

Context Length:

128000

Hardware Used:

BF16 format inference requires 8*80GB GPUs

Model Architecture:

Mixture-of-Experts with active parameters

Input Output

Input Format:

Prompt-based input

Accepted Modalities:

text

Output Format:

Model-generated text responses

Performance Tips:

Use of specified HF or vLLM frameworks for optimal inference.

LLM Name	DeepSeek Coder V2 Lite Instruct
Repository 🤗	https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct
Model Size	15.7b
Required VRAM	31.4 GB
Updated	2024-12-21
Maintainer	deepseek-ai
Model Type	deepseek_v2
Instruction-Based	Yes
Model Files	8.6 GB: 1-of-4 8.6 GB: 2-of-4 8.6 GB: 3-of-4 5.6 GB: 4-of-4
Generates Code	Yes
Model Architecture	DeepseekV2ForCausalLM
License	other
Context Length	163840
Model Max Length	163840
Transformers Version	4.39.3
Tokenizer Class	LlamaTokenizerFast
Beginning of Sentence Token	<｜begin▁of▁sentence｜>
End of Sentence Token	<｜end▁of▁sentence｜>
Vocabulary Size	102400
Torch Data Type	bfloat16

Quantized Models of the DeepSeek Coder V2 Lite Instruct

Model	Likes	Downloads	VRAM
...ek Coder V2 Lite Instruct GGUF	5	786	6 GB
...ek Coder V2 Lite Instruct GGUF	1	169	6 GB

Best Alternatives to DeepSeek Coder V2 Lite Instruct

Best Alternatives	Context / RAM	Downloads	Likes
...2 Lite Instruct FlashAttnPatch	160K / 31.4 GB	15	0

Rank the DeepSeek Coder V2 Lite Instruct 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

What open-source LLMs or SLMs are you in search of? 40013 in total.

Email us: info@extractum.io. Our Privacy Policy | Terms and Conditions | Suggest an improvement.

Our Social Media →

Original data from HuggingFace, OpenCompass and various public git repos.

Release v20241217

Support LLM Explorer