Text Generation
Transformers
TensorBoard
Safetensors
English
internlm2
feature-extraction
math
conversational
custom_code
Instructions to use MathGenie/InternLM2-SFT-SCDPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MathGenie/InternLM2-SFT-SCDPO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MathGenie/InternLM2-SFT-SCDPO", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MathGenie/InternLM2-SFT-SCDPO", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MathGenie/InternLM2-SFT-SCDPO with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MathGenie/InternLM2-SFT-SCDPO" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MathGenie/InternLM2-SFT-SCDPO", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/MathGenie/InternLM2-SFT-SCDPO
- SGLang
How to use MathGenie/InternLM2-SFT-SCDPO 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 "MathGenie/InternLM2-SFT-SCDPO" \ --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": "MathGenie/InternLM2-SFT-SCDPO", "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 "MathGenie/InternLM2-SFT-SCDPO" \ --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": "MathGenie/InternLM2-SFT-SCDPO", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use MathGenie/InternLM2-SFT-SCDPO with Docker Model Runner:
docker model run hf.co/MathGenie/InternLM2-SFT-SCDPO
| { | |
| "add_bos_token": true, | |
| "add_eos_token": false, | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1": { | |
| "content": "<s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": "</s>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92544": { | |
| "content": "<|user|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92545": { | |
| "content": "<|system|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92546": { | |
| "content": "<|assistant|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92547": { | |
| "content": "<|text|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92548": { | |
| "content": "<|code|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92549": { | |
| "content": "<|execution|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92550": { | |
| "content": "<|endofblock|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "92551": { | |
| "content": "<|endofmessage|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| "<|user|>", | |
| "<|system|>", | |
| "<|assistant|>", | |
| "<|text|>", | |
| "<|code|>", | |
| "<|execution|>", | |
| "<|endofblock|>", | |
| "<|endofmessage|>" | |
| ], | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_internlm2.InternLM2Tokenizer", | |
| "tokenization_internlm2_fast.InternLM2TokenizerFast" | |
| ] | |
| }, | |
| "bos_token": "<s>", | |
| "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>' }}{% elif message['role'] == 'system' %}\n{{ '<|system|>' }}{% elif message['role'] == 'assistant_correct' %}\n{{ '<|assistant|>' }}{% endif %}\n{% for block in message['content'] %}\n{% if block['type'] == 'text' %}\n{{ '<|text|>' }}{% elif block['type'] == 'code' %}\n{{ '<|code|>' }}{% elif block['type'] == 'execution' %}\n{{ '<|execution|>' }}{% endif %}\n{{ block['content'] + '<|endofblock|>' }}{% endfor %}\n{% if message['role'] != 'assistant_correct' %}\n{{ '<|endofmessage|>' }}{% endif %}{% endfor %}", | |
| "clean_up_tokenization_spaces": false, | |
| "decode_with_prefix_space": false, | |
| "eos_token": "</s>", | |
| "model_max_length": 2048, | |
| "pad_token": "</s>", | |
| "sp_model_kwargs": null, | |
| "tokenizer_class": "InternLM2Tokenizer", | |
| "unk_token": "<unk>" | |
| } | |