Instructions to use AaronLim/llama-3.2-3b-it-Library-ChatBot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AaronLim/llama-3.2-3b-it-Library-ChatBot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AaronLim/llama-3.2-3b-it-Library-ChatBot") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AaronLim/llama-3.2-3b-it-Library-ChatBot") model = AutoModelForCausalLM.from_pretrained("AaronLim/llama-3.2-3b-it-Library-ChatBot") 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
- vLLM
How to use AaronLim/llama-3.2-3b-it-Library-ChatBot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AaronLim/llama-3.2-3b-it-Library-ChatBot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AaronLim/llama-3.2-3b-it-Library-ChatBot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AaronLim/llama-3.2-3b-it-Library-ChatBot
- SGLang
How to use AaronLim/llama-3.2-3b-it-Library-ChatBot 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 "AaronLim/llama-3.2-3b-it-Library-ChatBot" \ --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": "AaronLim/llama-3.2-3b-it-Library-ChatBot", "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 "AaronLim/llama-3.2-3b-it-Library-ChatBot" \ --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": "AaronLim/llama-3.2-3b-it-Library-ChatBot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use AaronLim/llama-3.2-3b-it-Library-ChatBot with Docker Model Runner:
docker model run hf.co/AaronLim/llama-3.2-3b-it-Library-ChatBot
Upload tokenizer
Browse files- .gitattributes +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
tokenizer.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
CHANGED
|
@@ -2073,6 +2073,7 @@
|
|
| 2073 |
"chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
| 2074 |
"clean_up_tokenization_spaces": true,
|
| 2075 |
"eos_token": "<|im_end|>",
|
|
|
|
| 2076 |
"model_input_names": [
|
| 2077 |
"input_ids",
|
| 2078 |
"attention_mask"
|
|
|
|
| 2073 |
"chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
| 2074 |
"clean_up_tokenization_spaces": true,
|
| 2075 |
"eos_token": "<|im_end|>",
|
| 2076 |
+
"extra_special_tokens": {},
|
| 2077 |
"model_input_names": [
|
| 2078 |
"input_ids",
|
| 2079 |
"attention_mask"
|