Text Generation
Transformers
Safetensors
llama
Generated from Trainer
open-r1
dapo
trl
conversational
text-generation-inference
Instructions to use kangdawei/DAPO-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kangdawei/DAPO-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="kangdawei/DAPO-8B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("kangdawei/DAPO-8B") model = AutoModelForCausalLM.from_pretrained("kangdawei/DAPO-8B") 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]:])) - Inference
- Local Apps Settings
- vLLM
How to use kangdawei/DAPO-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kangdawei/DAPO-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kangdawei/DAPO-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/kangdawei/DAPO-8B
- SGLang
How to use kangdawei/DAPO-8B 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 "kangdawei/DAPO-8B" \ --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": "kangdawei/DAPO-8B", "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 "kangdawei/DAPO-8B" \ --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": "kangdawei/DAPO-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use kangdawei/DAPO-8B with Docker Model Runner:
docker model run hf.co/kangdawei/DAPO-8B
Training in progress, step 110
Browse files- adapter_model.safetensors +1 -1
- dynamic_sampling_log.txt +80 -0
- tokenizer.json +2 -2
adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 335605144
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b23e260d1a699c66322c5d307a7fc4ca9da7873e4615727d1a51806a976013dd
|
| 3 |
size 335605144
|
dynamic_sampling_log.txt
CHANGED
|
@@ -814,3 +814,83 @@ Step Attempts Total Prompts Valid Prompts Efficiency
|
|
| 814 |
99 3 18 6 33.3 %
|
| 815 |
99 2 12 6 50.0 %
|
| 816 |
99 3 18 6 33.3 %
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 814 |
99 3 18 6 33.3 %
|
| 815 |
99 2 12 6 50.0 %
|
| 816 |
99 3 18 6 33.3 %
|
| 817 |
+
100 2 12 6 50.0 %
|
| 818 |
+
100 3 18 6 33.3 %
|
| 819 |
+
100 3 18 6 33.3 %
|
| 820 |
+
100 3 18 6 33.3 %
|
| 821 |
+
100 1 6 6 100.0 %
|
| 822 |
+
100 6 36 6 16.7 %
|
| 823 |
+
100 3 18 6 33.3 %
|
| 824 |
+
100 2 12 6 50.0 %
|
| 825 |
+
101 3 18 6 33.3 %
|
| 826 |
+
101 4 24 6 25.0 %
|
| 827 |
+
101 4 24 6 25.0 %
|
| 828 |
+
101 5 30 6 20.0 %
|
| 829 |
+
101 4 24 6 25.0 %
|
| 830 |
+
101 3 18 6 33.3 %
|
| 831 |
+
101 1 6 6 100.0 %
|
| 832 |
+
101 2 12 6 50.0 %
|
| 833 |
+
102 5 30 6 20.0 %
|
| 834 |
+
102 2 12 6 50.0 %
|
| 835 |
+
102 2 12 6 50.0 %
|
| 836 |
+
102 3 18 6 33.3 %
|
| 837 |
+
102 3 18 6 33.3 %
|
| 838 |
+
102 4 24 6 25.0 %
|
| 839 |
+
102 6 36 6 16.7 %
|
| 840 |
+
102 6 36 6 16.7 %
|
| 841 |
+
103 3 18 6 33.3 %
|
| 842 |
+
103 1 6 6 100.0 %
|
| 843 |
+
103 7 42 6 14.3 %
|
| 844 |
+
103 8 48 6 12.5 %
|
| 845 |
+
103 6 36 6 16.7 %
|
| 846 |
+
103 3 18 6 33.3 %
|
| 847 |
+
103 3 18 6 33.3 %
|
| 848 |
+
103 6 36 6 16.7 %
|
| 849 |
+
104 3 18 6 33.3 %
|
| 850 |
+
104 1 6 6 100.0 %
|
| 851 |
+
104 2 12 6 50.0 %
|
| 852 |
+
104 2 12 6 50.0 %
|
| 853 |
+
104 5 30 6 20.0 %
|
| 854 |
+
104 5 30 6 20.0 %
|
| 855 |
+
104 5 30 6 20.0 %
|
| 856 |
+
104 1 6 6 100.0 %
|
| 857 |
+
105 8 48 6 12.5 %
|
| 858 |
+
105 2 12 6 50.0 %
|
| 859 |
+
105 3 18 6 33.3 %
|
| 860 |
+
105 4 24 6 25.0 %
|
| 861 |
+
105 6 36 6 16.7 %
|
| 862 |
+
105 3 18 6 33.3 %
|
| 863 |
+
105 4 24 6 25.0 %
|
| 864 |
+
105 2 12 6 50.0 %
|
| 865 |
+
106 4 24 6 25.0 %
|
| 866 |
+
106 4 24 6 25.0 %
|
| 867 |
+
106 4 24 6 25.0 %
|
| 868 |
+
106 11 66 6 9.1 %
|
| 869 |
+
106 5 30 6 20.0 %
|
| 870 |
+
106 3 18 6 33.3 %
|
| 871 |
+
106 5 30 6 20.0 %
|
| 872 |
+
106 9 54 6 11.1 %
|
| 873 |
+
107 6 36 6 16.7 %
|
| 874 |
+
107 10 60 6 10.0 %
|
| 875 |
+
107 7 42 6 14.3 %
|
| 876 |
+
107 5 30 6 20.0 %
|
| 877 |
+
107 4 24 6 25.0 %
|
| 878 |
+
107 5 30 6 20.0 %
|
| 879 |
+
107 2 12 6 50.0 %
|
| 880 |
+
107 6 36 6 16.7 %
|
| 881 |
+
108 1 6 6 100.0 %
|
| 882 |
+
108 1 6 6 100.0 %
|
| 883 |
+
108 4 24 6 25.0 %
|
| 884 |
+
108 3 18 6 33.3 %
|
| 885 |
+
108 11 66 6 9.1 %
|
| 886 |
+
108 1 6 6 100.0 %
|
| 887 |
+
108 4 24 6 25.0 %
|
| 888 |
+
108 1 6 6 100.0 %
|
| 889 |
+
109 2 12 6 50.0 %
|
| 890 |
+
109 1 6 6 100.0 %
|
| 891 |
+
109 2 12 6 50.0 %
|
| 892 |
+
109 2 12 6 50.0 %
|
| 893 |
+
109 10 60 6 10.0 %
|
| 894 |
+
109 5 30 6 20.0 %
|
| 895 |
+
109 3 18 6 33.3 %
|
| 896 |
+
109 5 30 6 20.0 %
|
tokenizer.json
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:26c881aaf4ef935b1516ec79ad6405dd2a459f2b5d431a8a4a1399c92f3ba022
|
| 3 |
+
size 17209711
|