Instructions to use matteoangeloni/EduDolphin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use matteoangeloni/EduDolphin with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="matteoangeloni/EduDolphin")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("matteoangeloni/EduDolphin")
model = AutoModelForCausalLM.from_pretrained("matteoangeloni/EduDolphin", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use matteoangeloni/EduDolphin with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "matteoangeloni/EduDolphin"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "matteoangeloni/EduDolphin",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/matteoangeloni/EduDolphin

SGLang

How to use matteoangeloni/EduDolphin with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "matteoangeloni/EduDolphin" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "matteoangeloni/EduDolphin",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "matteoangeloni/EduDolphin" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "matteoangeloni/EduDolphin",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Unsloth Desktop
Docker Model Runner
How to use matteoangeloni/EduDolphin with Docker Model Runner:
```
docker model run hf.co/matteoangeloni/EduDolphin
```

matteoangeloni commited on Sep 5, 2025

Commit

8806933

verified ·

1 Parent(s): 32fd31d

Update README.md

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README.md CHANGED Viewed

@@ -5,9 +5,11 @@ tags:
 - transformers
 - unsloth
 - llama
 license: apache-2.0
 language:
 - en
 ---
 # EduDolphin 🐬📚
@@ -215,4 +217,4 @@ Thanks to **Unsloth** for efficient fine‑tuning tooling, **Hugging Face TRL**
 pip install --upgrade transformers accelerate
 # Optional (for 4-bit merges)
 pip install bitsandbytes
-```

 - transformers
 - unsloth
 - llama
+- educational
 license: apache-2.0
 language:
 - en
+- it
 ---
 # EduDolphin 🐬📚
 pip install --upgrade transformers accelerate
 # Optional (for 4-bit merges)
 pip install bitsandbytes
+```