Name: Tulpar 7B V0
Author: HyperbeeAI

Tulpar 7B V0 is an open-source language model by HyperbeeAI. Features: 7b LLM, VRAM: 27GB, Context: 4K, License: llama2, HF Score: 52.7, LLM Explorer Score: 0.13, Arc: 56.3, HellaSwag: 79, MMLU: 52.6, TruthfulQA: 51.7, WinoGrande: 73.9, GSM8K: 2.7.

Autotrain compatible En Endpoints compatible Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/HyperbeeAI/Tulpar-7b-v0

Tulpar 7B V0 Benchmarks

ARC: 56.31 vs 96.7 (so35)^-41.8%

HellaSwag: 79.01 vs 95.3 (gpt4)^-17.1%

MMLU: 52.55 vs 88.3 (so35)^-40.5%

TruthfulQA: 51.68 vs 59 (gpt4)^-12.4%

WinoGrande: 73.88 vs 87.5 (gpt4)^-15.6%

GSM8K: 2.73 vs 96.4 (so35)^-97.2%

LLME Score: 0.13388

^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)

🌟 Advertise your project 🚀

Tulpar 7B V0 Parameters and Internals

Model Type

text_generation

Use Cases

Areas:

research, commercial applications

Limitations:

Language-related scenarios not covered besides English.

Additional Notes

Model image can be found at provided thumbnail URL.

Supported Languages

en (primary)

Training Details

Data Sources:

GPT-4 generated datasets, curated datasets like Airoboros and Platypus

Methodology:

filtered and preprocessed instruction finetuning

Model Architecture:

LLama2-7b

Responsible Ai Considerations

Fairness:

The model is finetuned only in English and all language-related scenarios are not covered.

Transparency:

No transparency guarantees for ethical, accurate, unbiased, objective responses.

Mitigation Strategies:

Safety tests are advised before deployment for specific use cases.

Input Output

Input Format:

Structured prompts with User and Assistant designations or Question and Answer format.

Accepted Modalities:

text

Output Format:

Text responses fitting the query context.

LLM Name	Tulpar 7B V0
Repository 🤗	https://huggingface.co/HyperbeeAI/Tulpar-7b-v0
Model Size	7b
Required VRAM	27 GB
Updated	2025-09-23
Maintainer	HyperbeeAI
Model Type	llama
Model Files	9.9 GB: 1-of-3 9.9 GB: 2-of-3 7.2 GB: 3-of-3
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float32

Quantized Models of the Tulpar 7B V0

Model	Likes	Downloads	VRAM
Tulpar 7B V0 AWQ	1	6	3 GB
Tulpar 7B V0 GGUF	3	67	2 GB
Tulpar 7B V0 GPTQ	2	6	3 GB

Best Alternatives to Tulpar 7B V0

Best Alternatives	Context / RAM	Downloads
124	1024K / 16.1 GB	93
162	1024K / 16.1 GB	60
157	1024K / 16.1 GB	101
118	1024K / 16.1 GB	15
A5.4	1024K / 16.1 GB	12
A6 L	1024K / 16.1 GB	201
A3.4	1024K / 16.1 GB	13
A2.4	1024K / 16.1 GB	12
M	1024K / 16.1 GB	127
2 Very Sci Fi	1024K / 16.1 GB	317

Note: green Score (e.g. "73.2") means that the model is better than HyperbeeAI/Tulpar-7b-v0.

Rank the Tulpar 7B V0 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? 52394 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.

Check out Ag3ntum — our secure, self-hosted AI agent for server management.

Release v20260328a

Support LLM Explorer

Tulpar 7B V0 by HyperbeeAI

» All LLMs » HyperbeeAI » Tulpar 7B V0 URL Share it on