Instructions to use pankajmathur/RenCoder-Ministral-8B-Instruct-2410 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pankajmathur/RenCoder-Ministral-8B-Instruct-2410 with Transformers:

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

pipe = pipeline("text-generation", model="pankajmathur/RenCoder-Ministral-8B-Instruct-2410")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pankajmathur/RenCoder-Ministral-8B-Instruct-2410")
model = AutoModelForCausalLM.from_pretrained("pankajmathur/RenCoder-Ministral-8B-Instruct-2410")
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 pankajmathur/RenCoder-Ministral-8B-Instruct-2410 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pankajmathur/RenCoder-Ministral-8B-Instruct-2410"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pankajmathur/RenCoder-Ministral-8B-Instruct-2410",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/pankajmathur/RenCoder-Ministral-8B-Instruct-2410

SGLang

How to use pankajmathur/RenCoder-Ministral-8B-Instruct-2410 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 "pankajmathur/RenCoder-Ministral-8B-Instruct-2410" \
    --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": "pankajmathur/RenCoder-Ministral-8B-Instruct-2410",
		"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 "pankajmathur/RenCoder-Ministral-8B-Instruct-2410" \
        --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": "pankajmathur/RenCoder-Ministral-8B-Instruct-2410",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use pankajmathur/RenCoder-Ministral-8B-Instruct-2410 with Docker Model Runner:
```
docker model run hf.co/pankajmathur/RenCoder-Ministral-8B-Instruct-2410
```

pankajmathur commited on Dec 12, 2025

Commit

37d280d

verified ·

1 Parent(s): d318215

Upload params.json with huggingface_hub

Browse files

Files changed (1) hide show

params.json +13 -0

params.json ADDED Viewed

	@@ -0,0 +1,13 @@

+{
+    "dim": 4096,
+    "n_layers": 36,
+    "head_dim": 128,
+    "hidden_dim": 12288,
+    "n_heads": 32,
+    "n_kv_heads": 8,
+    "norm_eps": 1e-05,
+    "vocab_size": 131072,
+    "rope_theta": 100000000.0,
+    "sliding_window": [null, 32768, 32768, 32768],
+    "max_position_embeddings": 131072
+}