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README.md

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+---
+license: llama3
+tags:
+- function-calling
+---
+
+# FireFunction V2: Fireworks Function Calling Model
+
+[**Try on Fireworks**](https://fireworks.ai/models/fireworks/firefunction-v2) | [**API Docs**](https://readme.fireworks.ai/docs/function-calling) | [**Demo App**](https://functional-chat.vercel.app/) | [**Discord**](https://discord.gg/mMqQxvFD9A)
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/64b6f3a72f5a966b9722de88/nJNtxLzWswBDKK1iOZblb.png" alt="firefunction" width="400"/>
+
+FireFunction is a state-of-the-art function calling model with a commercially viable license. View detailed info in our [announcement blog](https://fireworks.ai/blog/firefunction-v2-launch-post). Key info and highlights:
+
+**Comparison with other models:**
+- Competitive with GPT-4o at function-calling, scoring 0.81 vs 0.80 on a medley of public evaluations
+- Trained on Llama 3 and retains Llama 3’s conversation and instruction-following capabilities, scoring 0.84 vs Llama 3’s 0.89 on MT bench
+- Significant quality improvements over FireFunction v1 across the broad range of metrics
+
+
+**General info:**
+
+🐾 Successor of the [FireFunction](https://fireworks.ai/models/fireworks/firefunction-v1) model
+
+🔆 Support of parallel function calling (unlike FireFunction v1) and good instruction following
+
+💡 Hosted on the [Fireworks](https://fireworks.ai/models/fireworks/firefunction-v2) platform at < 10% of the cost of GPT 4o and 2x the speed
+
+
+
+
+## Intended Use and Limitations
+
+### Supported usecases
+The model was tuned to perfom well on a range of usecases including:
+ * general instruction following
+ * multi-turn chat mixing vanilla messages with function calls
+ * single- and parallel function calling
+ * up to 20 function specs supported at once
+ * structured information extraction
+   
+The model has an 8k context window, like Llama 3
+
+### Out-of-Scope Use
+The model was not optimized for the following use cases:
+  * 100+ function specs
+  * nested function calling
+
+## Metrics
+
+| Benchmark                          | Firefunction v1 | Firefunction v2 | Llama 3 70b Instruct | Gpt-4o |
+|:-----------------------------------|:----------------|:----------------|:---------------------|:-------|
+| Gorilla simple                     | 0.91            | 0.94            | 0.925                | 0.88   |
+| Gorilla multiple_function          | 0.92            | 0.91            | 0.86                 | 0.91   |
+| Gorilla parallel_function          | 0               | 0.9             | 0.86                 | 0.89   |
+| Gorilla parallel_multiple_function | 0               | 0.8             | 0.615                | 0.72   |
+| Nexus parallel                     | 0.38            | 0.53            | 0.3                  | 0.47   |
+| Mtbench                            | 0.73            | 0.84            | 0.89                 | 0.93   |
+| Average                            | 0.49            | 0.82            | 0.74                 | 0.8    |
+
+## Example Usage
+
+See [documentation](https://readme.fireworks.ai/docs/function-calling) for more detail.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import json
+from datetime import datetime
+
+device = "cuda" # the device to load the model onto
+
+model = AutoModelForCausalLM.from_pretrained("fireworks-ai/firefunction-v2", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("fireworks-ai/firefunction-v2")
+
+function_spec = [
+    {
+        "name": "get_stock_price",
+        "description": "Get the current stock price",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "symbol": {
+                    "type": "string",
+                    "description": "The stock symbol, e.g. AAPL, GOOG"
+                }
+            },
+            "required": [
+                "symbol"
+            ]
+        }
+    },
+    {
+        "name": "check_word_anagram",
+        "description": "Check if two words are anagrams of each other",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "word1": {
+                    "type": "string",
+                    "description": "The first word"
+                },
+                "word2": {
+                    "type": "string",
+                    "description": "The second word"
+                }
+            },
+            "required": [
+                "word1",
+                "word2"
+            ]
+        }
+    }
+]
+functions = json.dumps(function_spec, indent=4)
+
+messages = [
+    {'role': 'system', 'content': 'You are a helpful assistant with access to functions. Use them if required.'},
+    {'role': 'user', 'content': 'Hi, can you tell me the current stock price of google and netflix?'}
+]
+
+now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+
+model_inputs = tokenizer.apply_chat_template(messages, functions=functions, datetime=now, return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(model_inputs, max_new_tokens=128)
+decoded = tokenizer.batch_decode(generated_ids)
+print(decoded[0])
+```
+
+## Resources
+* [Fireworks discord with function calling channel](https://discord.gg/mMqQxvFD9A)
+* [Documentation](https://readme.fireworks.ai/docs/function-calling)
+* [Demo app](https://functional-chat.vercel.app/)
+* [Try in Fireworks prompt playground UI](https://fireworks.ai/models/fireworks/firefunction-v2)

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