Fireworks-ai inference support 🔥 (#2677)

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Co-authored-by: Célina <[email protected]>

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Co-authored-by: burtenshaw <[email protected]>

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Co-authored-by: Vaibhavs10 <[email protected]>
Co-authored-by: Célina <[email protected]>
Co-authored-by: Wauplin <[email protected]>
Co-authored-by: Lucain <[email protected]>
Co-authored-by: burtenshaw <[email protected]>

_blog.yml

@@ -5530,4 +5530,13 @@
     - math-verify
     - open-llm-leaderboard
     - leaderboard
-    - evaluation
+    - evaluation
+
+- local: fireworks-ai
+  title: "Welcome Fireworks.ai on the Hub"
+  author: julien-c
+  thumbnail: /blog/assets/inference-providers/welcome-fireworks-2.jpg
+  date: Feb 14, 2025
+  tags:
+    - announcement
+    - hub

fireworks-ai.md

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+---
+title: "Welcome Fireworks.ai on the Hub 🎆"
+thumbnail: /blog/assets/inference-providers/welcome-fireworks-2.jpg
+authors:
+- user: teofeliu
+  guest: true
+  org: fireworks-ai
+- user: shaunak-fireworks
+  guest: true
+  org: fireworks-ai
+- user: julien-c
+---
+
+Following our recent announcement on [Inference Providers on the Hub](https://huggingface.co/blog/inference-providers), we're thrilled to share that **Fireworks.ai** is now a supported Inference Provider on HF Hub!
+
+[Fireworks.ai](https://fireworks.ai) delivers blazing-fast serverless inference directly on model pages—making it easier than ever to deploy and experiment with your favorite models.
+
+Among others, starting now, you can run serverless inference to the following models via Fireworks.ai:
+
+- [deepseek-ai/DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1)
+- [deepseek-ai/DeepSeek-V3](https://huggingface.co/deepseek-ai/DeepSeek-V3)
+- [mistralai/Mistral-Small-24B-Instruct-2501](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501)
+- [Qwen/Qwen2.5-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct)
+- [meta-llama/Llama-3.2-90B-Vision-Instruct](https://huggingface.co/meta-llama/Llama-3.2-90B-Vision-Instruct)
+
+and many more, you can find the full list [here](https://huggingface.co/models?inference_provider=fireworks-ai).
+
+Light up your projects with Fireworks.ai today!
+
+<img src="https://huggingface.co/blog/inference-providers/welcome-fireworks-2.jpg" alt="Fireworks.ai supported as Inference Provider on Hugging Face"/>
+
+## How it works
+
+### In the website UI
+
+![Fireworks.ai inference provider UI](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/inference-providers/fireworks.png)
+
+Search for all models supported by Fireworks on HF **[here](https://huggingface.co/models?inference_provider=fireworks-ai)**.
+
+### From the client SDKs
+
+#### from Python, using huggingface_hub
+
+The following example shows how to use DeepSeek-R1 using Fireworks.ai as your inference provider. You can use a [Hugging Face token](https://huggingface.co/settings/tokens) for automatic routing through Hugging Face, or your own Fireworks.ai API key if you have one.
+
+Install `huggingface_hub` from source: 
+
+```bash
+pip install git+https://github.com/huggingface/huggingface_hub
+```
+
+Use the `huggingface_hub` python library to call Fireworks.ai endpoints by defining the `provider` parameter.
+
+```python
+from huggingface_hub import InferenceClient
+
+client = InferenceClient(
+    provider="fireworks-ai",
+    api_key="xxxxxxxxxxxxxxxxxxxxxxxx"
+)
+
+messages = [
+    {
+        "role": "user",
+        "content": "What is the capital of France?"
+    }
+]
+
+completion = client.chat.completions.create(
+    model="deepseek-ai/DeepSeek-R1", 
+    messages=messages, 
+    max_tokens=500
+)
+
+print(completion.choices[0].message)
+```
+
+#### from JS using @huggingface/inference
+
+```js
+import { HfInference } from "@huggingface/inference";
+
+const client = new HfInference("xxxxxxxxxxxxxxxxxxxxxxxx");
+
+const chatCompletion = await client.chatCompletion({
+    model: "deepseek-ai/DeepSeek-R1",
+    messages: [
+        {
+            role: "user",
+            content: "How to make extremely spicy Mayonnaise?"
+        }
+    ],
+    provider: "fireworks-ai",
+    max_tokens: 500
+});
+
+console.log(chatCompletion.choices[0].message);
+```
+
+### From HTTP calls
+
+Here's how you can call Llama-3.3-70B-Instruct using Fireworks.ai as the inference provider via cURL.
+
+```
+curl 'https://router.huggingface.co/fireworks-ai/v1/chat/completions' \
+-H 'Authorization: Bearer xxxxxxxxxxxxxxxxxxxxxxxx' \
+-H 'Content-Type: application/json' \
+--data '{
+    "model": "Llama-3.3-70B-Instruct",
+    "messages": [
+        {
+            "role": "user",
+            "content": "What is the meaning of life if you were a dog?"
+        }
+    ],
+    "max_tokens": 500,
+    "stream": false
+}'
+```
+
+## Billing
+
+For direct requests, i.e. when you use a Fireworks key, you are billed directly on your Fireworks account.
+
+For routed requests, i.e. when you authenticate via the hub, you'll only pay the standard Fireworks API rates. There's no additional markup from us, we just pass through the provider costs directly. (In the future, we may establish revenue-sharing agreements with our provider partners.)
+
+Important Note ‼️ PRO users get $2 worth of Inference credits every month. You can use them across providers. 🔥
+
+Subscribe to the [Hugging Face PRO plan](https://hf.co/subscribe/pro) to get access to Inference credits, ZeroGPU, Spaces Dev Mode, 20x higher limits, and more.