Instructions to use Veiterr/MNLP_M2_dpo_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Veiterr/MNLP_M2_dpo_model with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Veiterr/MNLP_M2_dpo_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Veiterr/MNLP_M2_dpo_model")
model = AutoModelForCausalLM.from_pretrained("Veiterr/MNLP_M2_dpo_model", 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 Veiterr/MNLP_M2_dpo_model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Veiterr/MNLP_M2_dpo_model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Veiterr/MNLP_M2_dpo_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Veiterr/MNLP_M2_dpo_model

SGLang

How to use Veiterr/MNLP_M2_dpo_model 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 "Veiterr/MNLP_M2_dpo_model" \
    --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": "Veiterr/MNLP_M2_dpo_model",
		"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 "Veiterr/MNLP_M2_dpo_model" \
        --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": "Veiterr/MNLP_M2_dpo_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Veiterr/MNLP_M2_dpo_model with Docker Model Runner:
```
docker model run hf.co/Veiterr/MNLP_M2_dpo_model
```

Veiterr commited on May 27, 2025

Commit

df74cd8

verified ·

1 Parent(s): 115d2b8

Upload Qwen3ForCausalLM

Browse files

Files changed (3) hide show

config.json +2 -2
generation_config.json +2 -9
model.safetensors +1 -1

config.json CHANGED Viewed

@@ -5,13 +5,13 @@
   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 151643,
-  "eos_token_id": 151645,
   "head_dim": 128,
   "hidden_act": "silu",
   "hidden_size": 1024,
   "initializer_range": 0.02,
   "intermediate_size": 3072,
-  "max_position_embeddings": 40960,
   "max_window_layers": 28,
   "model_type": "qwen3",
   "num_attention_heads": 16,

   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 151643,
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   "head_dim": 128,
   "hidden_act": "silu",
   "hidden_size": 1024,
   "initializer_range": 0.02,
   "intermediate_size": 3072,
+  "max_position_embeddings": 32768,
   "max_window_layers": 28,
   "model_type": "qwen3",
   "num_attention_heads": 16,

generation_config.json CHANGED Viewed

@@ -1,13 +1,6 @@
 {
   "bos_token_id": 151643,
-  "do_sample": true,
-  "eos_token_id": [
-    151645,
-    151643
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-  "temperature": 0.6,
-  "top_k": 20,
-  "top_p": 0.95,
   "transformers_version": "4.51.3"
 }

 {
   "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
   "transformers_version": "4.51.3"
 }

model.safetensors CHANGED Viewed

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