Instructions to use gbennani/MNLP_M2_RAG_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gbennani/MNLP_M2_RAG_model with Transformers:

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

pipe = pipeline("text-generation", model="gbennani/MNLP_M2_RAG_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gbennani/MNLP_M2_RAG_model")
model = AutoModelForCausalLM.from_pretrained("gbennani/MNLP_M2_RAG_model")
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 gbennani/MNLP_M2_RAG_model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gbennani/MNLP_M2_RAG_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": "gbennani/MNLP_M2_RAG_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/gbennani/MNLP_M2_RAG_model

SGLang

How to use gbennani/MNLP_M2_RAG_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 "gbennani/MNLP_M2_RAG_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": "gbennani/MNLP_M2_RAG_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 "gbennani/MNLP_M2_RAG_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": "gbennani/MNLP_M2_RAG_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use gbennani/MNLP_M2_RAG_model with Docker Model Runner:
```
docker model run hf.co/gbennani/MNLP_M2_RAG_model
```

gbennani commited on Jun 5, 2025

Commit

074c3b7

verified ·

1 Parent(s): cd0a847

Training in progress, step 1000

Browse files

Files changed (3) hide show

model.safetensors +1 -1
tokenizer.json +2 -2
training_args.bin +1 -1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:835299db86b7882b5afc51206deabbd371d4d4f4fe6e1083beacbbd71e00d8bc
 size 2384234968

 version https://git-lfs.github.com/spec/v1
+oid sha256:916fb5cc0110c15f3cdeb8b55764af0cd5d1269f5881f5c3a37c00c0a96375ac
 size 2384234968

tokenizer.json CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
-size 11422654

 version https://git-lfs.github.com/spec/v1
+oid sha256:aec0af1bf56f5a5236a7028a4d9a0c846c57b43637a9b0c4ee6e0f9031d65ce1
+size 11422930

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ffe742a13875eb760831730cff205bd03e1be7d699ea53502a83598880db97ae
 size 5304

 version https://git-lfs.github.com/spec/v1
+oid sha256:eac19815aef3dbfecd4a36c062c869733c46b46bd5b50ab5f58db5b595581827
 size 5304