Instructions to use notzero/qwen1_5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notzero/qwen1_5b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="notzero/qwen1_5b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("notzero/qwen1_5b") model = AutoModelForCausalLM.from_pretrained("notzero/qwen1_5b", device_map="auto") 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 notzero/qwen1_5b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "notzero/qwen1_5b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "notzero/qwen1_5b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/notzero/qwen1_5b
- SGLang
How to use notzero/qwen1_5b 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 "notzero/qwen1_5b" \ --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": "notzero/qwen1_5b", "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 "notzero/qwen1_5b" \ --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": "notzero/qwen1_5b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio
How to use notzero/qwen1_5b 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 notzero/qwen1_5b 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 notzero/qwen1_5b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for notzero/qwen1_5b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="notzero/qwen1_5b", max_seq_length=2048, ) - Docker Model Runner
How to use notzero/qwen1_5b with Docker Model Runner:
docker model run hf.co/notzero/qwen1_5b
Upload tokenizer
Browse files- added_tokens.json +0 -2
- tokenizer_config.json +0 -16
added_tokens.json
CHANGED
|
@@ -1,7 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"</think>": 151666,
|
| 3 |
"</tool_call>": 151658,
|
| 4 |
-
"<think>": 151665,
|
| 5 |
"<tool_call>": 151657,
|
| 6 |
"<|box_end|>": 151649,
|
| 7 |
"<|box_start|>": 151648,
|
|
|
|
| 1 |
{
|
|
|
|
| 2 |
"</tool_call>": 151658,
|
|
|
|
| 3 |
"<tool_call>": 151657,
|
| 4 |
"<|box_end|>": 151649,
|
| 5 |
"<|box_start|>": 151648,
|
tokenizer_config.json
CHANGED
|
@@ -177,22 +177,6 @@
|
|
| 177 |
"rstrip": false,
|
| 178 |
"single_word": false,
|
| 179 |
"special": false
|
| 180 |
-
},
|
| 181 |
-
"151665": {
|
| 182 |
-
"content": "<think>",
|
| 183 |
-
"lstrip": false,
|
| 184 |
-
"normalized": true,
|
| 185 |
-
"rstrip": false,
|
| 186 |
-
"single_word": false,
|
| 187 |
-
"special": false
|
| 188 |
-
},
|
| 189 |
-
"151666": {
|
| 190 |
-
"content": "</think>",
|
| 191 |
-
"lstrip": false,
|
| 192 |
-
"normalized": true,
|
| 193 |
-
"rstrip": false,
|
| 194 |
-
"single_word": false,
|
| 195 |
-
"special": false
|
| 196 |
}
|
| 197 |
},
|
| 198 |
"additional_special_tokens": [
|
|
|
|
| 177 |
"rstrip": false,
|
| 178 |
"single_word": false,
|
| 179 |
"special": false
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 180 |
}
|
| 181 |
},
|
| 182 |
"additional_special_tokens": [
|