Add pipeline tag, library name, and sample usage
#1
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -2,26 +2,49 @@
|
|
| 2 |
base_model:
|
| 3 |
- meta-llama/Llama-3.2-3B-Instruct
|
| 4 |
license: mit
|
|
|
|
|
|
|
| 5 |
---
|
| 6 |
|
| 7 |
# Sequential-Scaled-Critic-Llama3.2-3B
|
| 8 |
|
| 9 |
[π Project Page](https://recursivemas.github.io) | [π» Code](https://github.com/RecursiveMAS/RecursiveMAS) | [π Paper](https://arxiv.org/abs/2604.25917)
|
| 10 |
|
| 11 |
-
|
| 12 |
-
|
|
|
|
| 13 |
|
| 14 |
## Model Details
|
| 15 |
|
| 16 |
| Item | Description |
|
| 17 |
|---|---|
|
| 18 |
-
| Model | Sequential-Scaled-Critic-Llama3.2-3B |
|
| 19 |
-
| Collaboration Style | Sequential-Scaled |
|
| 20 |
-
| Agent Role | Critic Agent |
|
| 21 |
-
| Base Model |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 22 |
|
| 23 |
-
|
| 24 |
-
For detailed usage instructions, please refer to our [GitHub repository](https://github.com/RecursiveMAS/RecursiveMAS).
|
| 25 |
|
| 26 |
## Model Collections for RecursiveMAS
|
| 27 |
|
|
|
|
| 2 |
base_model:
|
| 3 |
- meta-llama/Llama-3.2-3B-Instruct
|
| 4 |
license: mit
|
| 5 |
+
pipeline_tag: text-generation
|
| 6 |
+
library_name: transformers
|
| 7 |
---
|
| 8 |
|
| 9 |
# Sequential-Scaled-Critic-Llama3.2-3B
|
| 10 |
|
| 11 |
[π Project Page](https://recursivemas.github.io) | [π» Code](https://github.com/RecursiveMAS/RecursiveMAS) | [π Paper](https://arxiv.org/abs/2604.25917)
|
| 12 |
|
| 13 |
+
**RecursiveMAS** is a multi-agent framework that scales agent collaboration through **latent-space recursion**. It treats a multi-agent system as a unified recursive computation, where heterogeneous agents iteratively exchange, refine, and evolve their latent states across recursion rounds.
|
| 14 |
+
|
| 15 |
+
In the **Sequential-Scaled** setting, this **Critic Agent** is responsible for reviewing and refining the initial plan produced by the Planner Agent, which is then passed to the Solver Agent for final solution generation.
|
| 16 |
|
| 17 |
## Model Details
|
| 18 |
|
| 19 |
| Item | Description |
|
| 20 |
|---|---|
|
| 21 |
+
| **Model** | Sequential-Scaled-Critic-Llama3.2-3B |
|
| 22 |
+
| **Collaboration Style** | Sequential-Scaled |
|
| 23 |
+
| **Agent Role** | Critic Agent |
|
| 24 |
+
| **Base Model** | [Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) |
|
| 25 |
+
|
| 26 |
+
β οΈ **Note:** This checkpoint is a **role-specific agent** in [RecursiveMAS](https://arxiv.org/abs/2604.25917), rather than a standalone model intended for plain-text generation.
|
| 27 |
+
|
| 28 |
+
## Usage
|
| 29 |
+
|
| 30 |
+
To use this model within the RecursiveMAS framework, you can load the entire multi-agent system as follows:
|
| 31 |
+
|
| 32 |
+
```python
|
| 33 |
+
from system_loader import load_mas_system
|
| 34 |
+
|
| 35 |
+
# Load the whole MAS pipeline
|
| 36 |
+
mas = load_mas_system(
|
| 37 |
+
style="sequential_scaled",
|
| 38 |
+
device="cuda",
|
| 39 |
+
trust_remote_code=True,
|
| 40 |
+
)
|
| 41 |
+
|
| 42 |
+
planner = mas.agents["planner"].model
|
| 43 |
+
critic = mas.agents["critic"].model
|
| 44 |
+
solver = mas.agents["solver"].model
|
| 45 |
+
```
|
| 46 |
|
| 47 |
+
For detailed setup and inference instructions, please refer to the [GitHub repository](https://github.com/RecursiveMAS/RecursiveMAS).
|
|
|
|
| 48 |
|
| 49 |
## Model Collections for RecursiveMAS
|
| 50 |
|