Instructions to use NousResearch/Hermes-4-70B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NousResearch/Hermes-4-70B with Transformers:

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

pipe = pipeline("text-generation", model="NousResearch/Hermes-4-70B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NousResearch/Hermes-4-70B")
model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-4-70B", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use NousResearch/Hermes-4-70B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NousResearch/Hermes-4-70B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NousResearch/Hermes-4-70B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NousResearch/Hermes-4-70B

SGLang

How to use NousResearch/Hermes-4-70B 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 "NousResearch/Hermes-4-70B" \
    --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": "NousResearch/Hermes-4-70B",
		"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 "NousResearch/Hermes-4-70B" \
        --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": "NousResearch/Hermes-4-70B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use NousResearch/Hermes-4-70B with Docker Model Runner:
```
docker model run hf.co/NousResearch/Hermes-4-70B
```

teknium

nielsr HF Staff commited on Sep 2, 2025

Commit

d5dec2b

verified ·

1 Parent(s): cbd3531

Add pipeline tag: text-generation (#4)

Browse files

- Add pipeline tag: text-generation (ff5e414ed7f767ce3744c86f1e8aa66d70315ddd)

Co-authored-by: Niels Rogge <[email protected]>

Files changed (1) hide show

README.md +5 -6

README.md CHANGED Viewed

@@ -1,7 +1,10 @@
 ---
 language:
 - en
 license: llama3
 tags:
 - Llama-3.1
 - instruct
@@ -18,18 +21,14 @@ tags:
 - long context
 - roleplaying
 - chat
-base_model: meta-llama/Meta-Llama-3.1-70B
-library_name: transformers
 widget:
 - example_title: Hermes 4
   messages:
   - role: system
-    content: >-
-      You are Hermes 4, a capable, neutrally-aligned assistant. Prefer concise,
       correct answers.
   - role: user
-    content: >-
-      Explain the difference between BFS and DFS to a new CS student.
 model-index:
 - name: Hermes-4-Llama-3.1-70B
   results: []

 ---
+base_model: meta-llama/Meta-Llama-3.1-70B
 language:
 - en
+library_name: transformers
 license: llama3
+pipeline_tag: text-generation
 tags:
 - Llama-3.1
 - instruct
 - long context
 - roleplaying
 - chat
 widget:
 - example_title: Hermes 4
   messages:
   - role: system
+    content: You are Hermes 4, a capable, neutrally-aligned assistant. Prefer concise,
       correct answers.
   - role: user
+    content: Explain the difference between BFS and DFS to a new CS student.
 model-index:
 - name: Hermes-4-Llama-3.1-70B
   results: []