Instructions to use thelamapi/next-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use thelamapi/next-14b with Transformers:

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

pipe = pipeline("text-generation", model="thelamapi/next-14b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("thelamapi/next-14b")
model = AutoModelForCausalLM.from_pretrained("thelamapi/next-14b")
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 thelamapi/next-14b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "thelamapi/next-14b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "thelamapi/next-14b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/thelamapi/next-14b

SGLang

How to use thelamapi/next-14b 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 "thelamapi/next-14b" \
    --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": "thelamapi/next-14b",
		"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 "thelamapi/next-14b" \
        --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": "thelamapi/next-14b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use thelamapi/next-14b with Docker Model Runner:
```
docker model run hf.co/thelamapi/next-14b
```

Lamapi commited on Nov 4, 2025

Commit

1bfc729

verified ·

1 Parent(s): 5e2c147

Update README.md

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README.md +16 -16

README.md CHANGED Viewed

@@ -97,29 +97,29 @@ Unlike vision-based models, **Next 14B focuses on pure cognitive performance**,
       <td><strong>Next 14B</strong></td>
       <td><strong>94.6</strong></td>
       <td><strong>83.2</strong></td>
-      <td><strong>95.8</strong></td>
-      <td><strong>85.7</strong></td>
     </tr>
     <tr>
       <td>Next 12B</td>
-      <td>91.8</td>
-      <td>78.4</td>
-      <td>94.3</td>
-      <td>81.2</td>
     </tr>
     <tr>
-      <td>GPT-4o</td>
-      <td>88.7</td>
-      <td>72.6</td>
-      <td>92.3</td>
-      <td>76.6</td>
     </tr>
     <tr>
-      <td>Claude Sonnet 4</td>
-      <td>~88.3</td>
-      <td>75.8</td>
-      <td>90.8</td>
-      <td>78.3</td>
     </tr>
   </tbody>
 </table>

       <td><strong>Next 14B</strong></td>
       <td><strong>94.6</strong></td>
       <td><strong>83.2</strong></td>
+      <td><strong>98.8</strong></td>
+      <td>92.7</td>
     </tr>
     <tr>
       <td>Next 12B</td>
+      <td>92.7</td>
+      <td>84.4</td>
+      <td>95.3</td>
+      <td>87.2</td>
     </tr>
     <tr>
+      <td>GPT-5</td>
+      <td>92.5</td>
+      <td>87.0</td>
+      <td>98.4</td>
+      <td><strong>96.0</strong></td>
     </tr>
     <tr>
+      <td>Claude Opus 4.1 (Thinking)</td>
+      <td>~92.0</td>
+      <td>87.8</td>
+      <td>84.7</td>
+      <td>95.4</td>
     </tr>
   </tbody>
 </table>