Text Generation
Transformers
Safetensors
Turkish
gpt2
Turkish
turkish
instruction-tuning
alpaca
conversational
text-generation-inference
Instructions to use ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1") model = AutoModelForMultimodalLM.from_pretrained("ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1") 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 ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1
- SGLang
How to use ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1 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 "ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1" \ --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": "ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1", "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 "ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1" \ --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": "ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1 with Docker Model Runner:
docker model run hf.co/ytu-ce-cosmos/turkish-gpt2-large-750m-instruct-v0.1
Update tokenizer_config.json
#11
by erndgn - opened
- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
|
@@ -20,7 +20,7 @@
|
|
| 20 |
}
|
| 21 |
},
|
| 22 |
"bos_token": "<|endoftext|>",
|
| 23 |
-
"chat_template": "{%
|
| 24 |
"clean_up_tokenization_spaces": true,
|
| 25 |
"eos_token": "<|stop|>",
|
| 26 |
"errors": "replace",
|
|
|
|
| 20 |
}
|
| 21 |
},
|
| 22 |
"bos_token": "<|endoftext|>",
|
| 23 |
+
"chat_template": "{% set message_count = messages|length %}{% if message_count >= 4 and messages[-4].role == 'user' %}{% set recent_messages = messages[-4:] %}{% elif message_count > 3 %}{% set recent_messages = messages[-3:] %}{% else %}{% set recent_messages = messages %}{% endif %}{% for message in recent_messages %}{% if message.role == 'user' %}### Kullanıcı:\n{{ message.content }}\n{% elif message.role == 'assistant' %}### Asistan:\n{{ message.content }}\n{% endif %}{% endfor %}{% if messages[-1]['role'] == 'user' %}### Asistan:\n{% endif %}",
|
| 24 |
"clean_up_tokenization_spaces": true,
|
| 25 |
"eos_token": "<|stop|>",
|
| 26 |
"errors": "replace",
|