Text Generation
Transformers
Safetensors
deepseek_v2
deepseek
mla
Mixture of Experts
fp8
group-quantization
compressed-tensors
conversational
custom_code
text-generation-inference
Instructions to use carlyou/DeepSeek-V2-Lite-FP8-Group with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carlyou/DeepSeek-V2-Lite-FP8-Group with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="carlyou/DeepSeek-V2-Lite-FP8-Group", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("carlyou/DeepSeek-V2-Lite-FP8-Group", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("carlyou/DeepSeek-V2-Lite-FP8-Group", trust_remote_code=True) 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 carlyou/DeepSeek-V2-Lite-FP8-Group with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "carlyou/DeepSeek-V2-Lite-FP8-Group" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "carlyou/DeepSeek-V2-Lite-FP8-Group", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/carlyou/DeepSeek-V2-Lite-FP8-Group
- SGLang
How to use carlyou/DeepSeek-V2-Lite-FP8-Group 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 "carlyou/DeepSeek-V2-Lite-FP8-Group" \ --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": "carlyou/DeepSeek-V2-Lite-FP8-Group", "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 "carlyou/DeepSeek-V2-Lite-FP8-Group" \ --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": "carlyou/DeepSeek-V2-Lite-FP8-Group", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use carlyou/DeepSeek-V2-Lite-FP8-Group with Docker Model Runner:
docker model run hf.co/carlyou/DeepSeek-V2-Lite-FP8-Group
File size: 1,006 Bytes
68c5c3a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | default_stage:
default_modifiers:
QuantizationModifier:
config_groups:
group_0:
targets: [Linear]
weights:
num_bits: 8
type: float
symmetric: true
group_size: 64
strategy: group
block_structure: null
dynamic: false
actorder: null
scale_dtype: null
zp_dtype: null
observer: memoryless_minmax
observer_kwargs: {}
input_activations:
num_bits: 8
type: float
symmetric: true
group_size: null
strategy: token
block_structure: null
dynamic: true
actorder: null
scale_dtype: null
zp_dtype: null
observer: null
observer_kwargs: {}
output_activations: null
format: null
targets: [Linear]
ignore: [lm_head]
bypass_divisibility_checks: false
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