Instructions to use nebius/EAGLE3-Llama-3.3-70B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nebius/EAGLE3-Llama-3.3-70B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="nebius/EAGLE3-Llama-3.3-70B-Instruct")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nebius/EAGLE3-Llama-3.3-70B-Instruct")
model = AutoModelForCausalLM.from_pretrained("nebius/EAGLE3-Llama-3.3-70B-Instruct", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nebius/EAGLE3-Llama-3.3-70B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nebius/EAGLE3-Llama-3.3-70B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nebius/EAGLE3-Llama-3.3-70B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/nebius/EAGLE3-Llama-3.3-70B-Instruct

SGLang

How to use nebius/EAGLE3-Llama-3.3-70B-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 "nebius/EAGLE3-Llama-3.3-70B-Instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nebius/EAGLE3-Llama-3.3-70B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "nebius/EAGLE3-Llama-3.3-70B-Instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nebius/EAGLE3-Llama-3.3-70B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use nebius/EAGLE3-Llama-3.3-70B-Instruct with Docker Model Runner:
```
docker model run hf.co/nebius/EAGLE3-Llama-3.3-70B-Instruct
```

astrlrd commited on Mar 4

Commit

34674c6

verified ·

1 Parent(s): 140a911

Update README.md

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README.md +31 -30

README.md CHANGED Viewed

@@ -9,37 +9,38 @@ tags:
 - inference-acceleration
 base_model: meta-llama/Llama-3.3-70B-Instruct
 license: cc-by-4.0
 model-index:
-  - name: nebius/EAGLE3-Llama-3.3-70B-Instruct
-    results:
-      - task:
-          type: text-generation
-        dataset:
-          name: MT-Bench
-          type: MT-Bench
-        metrics:
-          - name: Acceptance Length
-            type: Acceptance Length
-            value: 3.89
-      - task:
-          type: text-generation
-        dataset:
-          name: GSM8K
-          type: GSM8K
-        metrics:
-          - name: Acceptance Length
-            type: Acceptance Length
-            value: 5.01
-      - task:
-          type: text-generation
-        dataset:
-          name: HumanEval
-          type: HumanEval
-        metrics:
-          - name: Acceptance Length
-            type: Acceptance Length
-            value: 5.08
 ---
 ## Model Description

 - inference-acceleration
 base_model: meta-llama/Llama-3.3-70B-Instruct
 license: cc-by-4.0
 model-index:
+- name: nebius/EAGLE3-Llama-3.3-70B-Instruct
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      name: MT-Bench
+      type: MT-Bench
+    metrics:
+    - name: Acceptance Length
+      type: Acceptance Length
+      value: 3.89
+  - task:
+      type: text-generation
+    dataset:
+      name: GSM8K
+      type: GSM8K
+    metrics:
+    - name: Acceptance Length
+      type: Acceptance Length
+      value: 5.01
+  - task:
+      type: text-generation
+    dataset:
+      name: HumanEval
+      type: HumanEval
+    metrics:
+    - name: Acceptance Length
+      type: Acceptance Length
+      value: 5.08
+datasets:
+- nebius/Llama-3.3-70B-Instruct-Infinity-Instruct-0625
 ---
 ## Model Description