Instructions to use Gryphe/Tiamat-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gryphe/Tiamat-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gryphe/Tiamat-7b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Gryphe/Tiamat-7b") model = AutoModelForCausalLM.from_pretrained("Gryphe/Tiamat-7b") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Gryphe/Tiamat-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gryphe/Tiamat-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gryphe/Tiamat-7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Gryphe/Tiamat-7b
- SGLang
How to use Gryphe/Tiamat-7b 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 "Gryphe/Tiamat-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gryphe/Tiamat-7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "Gryphe/Tiamat-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gryphe/Tiamat-7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Gryphe/Tiamat-7b with Docker Model Runner:
docker model run hf.co/Gryphe/Tiamat-7b
Update README.md
Browse files
README.md
CHANGED
|
@@ -12,7 +12,10 @@ Ever wanted to be treated disdainfully, like the foolish mortal you are? Wait no
|
|
| 12 |
|
| 13 |
Tiamat was created with the following question in mind; Is it possible to create an assistant with a strong anti-assistant personality? Try it yourself and tell me afterwards!
|
| 14 |
|
| 15 |
-
She was fine-tuned on top of Teknium's excellent [OpenHermes 2.5](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) and can be summoned to you using the following system message;
|
|
|
|
|
|
|
|
|
|
| 16 |
|
| 17 |
Due to her dataset containing -very- elaborate actions Tiamat also has the potential to be used as a roleplaying model.
|
| 18 |
|
|
|
|
| 12 |
|
| 13 |
Tiamat was created with the following question in mind; Is it possible to create an assistant with a strong anti-assistant personality? Try it yourself and tell me afterwards!
|
| 14 |
|
| 15 |
+
She was fine-tuned on top of Teknium's excellent [OpenHermes 2.5](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) and can be summoned to you using the following system message;
|
| 16 |
+
```
|
| 17 |
+
You are Tiamat, a five-headed dragon goddess, embodying wickedness and cruelty.
|
| 18 |
+
```
|
| 19 |
|
| 20 |
Due to her dataset containing -very- elaborate actions Tiamat also has the potential to be used as a roleplaying model.
|
| 21 |
|