What are the hardware requirements for Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1?

Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1 requires approximately 5.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1?

Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1 by Yhyu13 — VRAM 5.6GB

Name: Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1
Author: Yhyu13

Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1 is an open-source language model by Yhyu13. Features: 2.8b LLM, VRAM: 5.6GB, License: mit, LLM Explorer Score: 0.1.

Conversational Custom code Endpoints compatible Phi-msft Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Yhyu13/dolphin-2_6-phi-2-sft-glaive-function-calling-v2-ep1

Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1 Parameters and Internals

Model Type

Merged model, Function calling

Additional Notes

This model should not be used in production due to limited prompt following ability in terms of function calling. Users are directed to a better function calling model by the same developers.

Training Details

Data Sources:

https://huggingface.co/datasets/Yhyu13/glaive-function-calling-v2-llama-factory-convert, https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2

Input Output

Input Format:

Function calls wrapped in XML tags for easier identification.

Output Format:

Function call results identified separately to treat as part of conversational response.

Performance Tips:

Use AST literal eval for JSON parsing if single quotes are used within the JSON string.

LLM Name	Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1
Repository 🤗	https://huggingface.co/Yhyu13/dolphin-2_6-phi-2-sft-glaive-function-calling-v2-ep1
Model Size	2.8b
Required VRAM	5.6 GB
Updated	2026-07-24
Maintainer	Yhyu13
Model Type	phi-msft
Model Files	5.0 GB: 1-of-2 0.6 GB: 2-of-2
Model Architecture	PhiForCausalLM
License	mit
Model Max Length	2048
Transformers Version	4.36.2
Tokenizer Class	CodeGenTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	51200
Torch Data Type	float16
Activation Function	gelu_new
Errors	replace

Rank the Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1 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

Best Alternatives to Dolphin 2 6 Phi 2 Sft Glaive Function Calling V2 Ep1

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MFANN3bv0.24	128K / 11.1 GB	6
MFANN3b	128K / 11.1 GB	86
MFANN3bv1.4	128K / 11.1 GB	8
MFANN Phigments Slerp V3.2	128K / 5.6 GB	6
MFANN3bv1.3	128K / 11.1 GB	14
MFANN3bv0.23	128K / 11.1 GB	10
MFANN3bv1.1	128K / 11.1 GB	10
MFANN3bv1.5	128K / 11.1 GB	8
MFANN Liminerity Slerp 4a	128K / 5.6 GB	7
MFANN3b Rebase	128K / 11.1 GB	7

Note: green Score (e.g. "73.2") means that the model is better than Yhyu13/dolphin-2_6-phi-2-sft-glaive-function-calling-v2-ep1.