Instructions to use FuseAI/FuseChat-Llama-3.1-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FuseAI/FuseChat-Llama-3.1-8B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="FuseAI/FuseChat-Llama-3.1-8B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FuseAI/FuseChat-Llama-3.1-8B-Instruct")
model = AutoModelForCausalLM.from_pretrained("FuseAI/FuseChat-Llama-3.1-8B-Instruct")
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 FuseAI/FuseChat-Llama-3.1-8B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FuseAI/FuseChat-Llama-3.1-8B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FuseAI/FuseChat-Llama-3.1-8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FuseAI/FuseChat-Llama-3.1-8B-Instruct

SGLang

How to use FuseAI/FuseChat-Llama-3.1-8B-Instruct 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 "FuseAI/FuseChat-Llama-3.1-8B-Instruct" \
    --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": "FuseAI/FuseChat-Llama-3.1-8B-Instruct",
		"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 "FuseAI/FuseChat-Llama-3.1-8B-Instruct" \
        --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": "FuseAI/FuseChat-Llama-3.1-8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FuseAI/FuseChat-Llama-3.1-8B-Instruct with Docker Model Runner:
```
docker model run hf.co/FuseAI/FuseChat-Llama-3.1-8B-Instruct
```

AALF commited on Feb 7, 2025

Commit

007f2da

verified ·

1 Parent(s): 2cc7f69

Update README.md

Browse files

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README.md +15 -8

README.md CHANGED Viewed

@@ -16,7 +16,8 @@ model-index:
       value: 72.05
       name: averaged accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -32,7 +33,8 @@ model-index:
       value: 30.85
       name: normalized accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -48,7 +50,8 @@ model-index:
       value: 7.02
       name: exact match
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -64,7 +67,8 @@ model-index:
       value: 7.38
       name: acc_norm
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -79,7 +83,8 @@ model-index:
       value: 6.15
       name: acc_norm
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -96,8 +101,11 @@ model-index:
       value: 30.37
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
 ---
 <p align="center" width="100%">
 </p>
@@ -526,5 +534,4 @@ Summarized results can be found [here](https://huggingface.co/datasets/open-llm-
 |MATH Lvl 5 (4-Shot)|     7.02|
 |GPQA (0-shot)      |     7.38|
 |MuSR (0-shot)      |     6.15|
-|MMLU-PRO (5-shot)  |    30.37|

       value: 72.05
       name: averaged accuracy
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 30.85
       name: normalized accuracy
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 7.02
       name: exact match
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 7.38
       name: acc_norm
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 6.15
       name: acc_norm
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 30.37
       name: accuracy
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=FuseAI%2FFuseChat-Llama-3.1-8B-Instruct
       name: Open LLM Leaderboard
+datasets:
+- FuseAI/FuseChat-3.0-DPO-Data
 ---
 <p align="center" width="100%">
 </p>
 |MATH Lvl 5 (4-Shot)|     7.02|
 |GPQA (0-shot)      |     7.38|
 |MuSR (0-shot)      |     6.15|
+|MMLU-PRO (5-shot)  |    30.37|