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

Libraries

How to use Terisara/student_Emo_PAD_Topic with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Terisara/student_Emo_PAD_Topic",
	filename="llama-3.2-3b-instruct.Q8_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Terisara/student_Emo_PAD_Topic with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Terisara/student_Emo_PAD_Topic:Q8_0
# Run inference directly in the terminal:
llama cli -hf Terisara/student_Emo_PAD_Topic:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Terisara/student_Emo_PAD_Topic:Q8_0
# Run inference directly in the terminal:
llama cli -hf Terisara/student_Emo_PAD_Topic:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Terisara/student_Emo_PAD_Topic:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf Terisara/student_Emo_PAD_Topic:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Terisara/student_Emo_PAD_Topic:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Terisara/student_Emo_PAD_Topic:Q8_0

Use Docker

docker model run hf.co/Terisara/student_Emo_PAD_Topic:Q8_0

LM Studio
Jan
Ollama
How to use Terisara/student_Emo_PAD_Topic with Ollama:
```
ollama run hf.co/Terisara/student_Emo_PAD_Topic:Q8_0
```

Unsloth Studio

How to use Terisara/student_Emo_PAD_Topic with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Terisara/student_Emo_PAD_Topic to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Terisara/student_Emo_PAD_Topic to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Terisara/student_Emo_PAD_Topic to start chatting

Atomic Chat new
Docker Model Runner
How to use Terisara/student_Emo_PAD_Topic with Docker Model Runner:
```
docker model run hf.co/Terisara/student_Emo_PAD_Topic:Q8_0
```

Lemonade

How to use Terisara/student_Emo_PAD_Topic with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Terisara/student_Emo_PAD_Topic:Q8_0

Run and chat with the model

lemonade run user.student_Emo_PAD_Topic-Q8_0

List all available models

lemonade list

student_Emo_PAD_Topic / tokenizer_config.json

Terisara

(Trained with Unsloth)

6fce5c3 verified 4 months ago

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	{
	"backend": "tokenizers",
	"bos_token": "<\|begin_of_text\|>",
	"eos_token": "<\|im_end\|>",
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "<\|finetune_right_pad_id\|>",
	"tokenizer_class": "TokenizersBackend",
	"unk_token": null,
	"chat_template": "{% if 'role' in messages[0] %}{% for message in messages %}{% if message['role'] == 'user' %}{{'<\|im_start\|>user\n' + message['content'] + '<\|im_end\|>\n'}}{% elif message['role'] == 'assistant' %}{{'<\|im_start\|>assistant\n' + message['content'] + '<\|im_end\|>\n' }}{% else %}{{ '<\|im_start\|>system\n' + message['content'] + '<\|im_end\|>\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<\|im_start\|>assistant\n' }}{% endif %}{% else %}{% for message in messages %}{% if message['from'] == 'human' %}{{'<\|im_start\|>user\n' + message['value'] + '<\|im_end\|>\n'}}{% elif message['from'] == 'gpt' %}{{'<\|im_start\|>assistant\n' + message['value'] + '<\|im_end\|>\n' }}{% else %}{{ '<\|im_start\|>system\n' + message['value'] + '<\|im_end\|>\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<\|im_start\|>assistant\n' }}{% endif %}{% endif %}"
	}