diff --git a/gallery/index.yaml b/gallery/index.yaml
index 833c4cccd764..dabde476923f 100644
--- a/gallery/index.yaml
+++ b/gallery/index.yaml
@@ -2120,6 +2120,37 @@
- filename: Llama-3.1-WhiteRabbitNeo-2-8B-Q4_K_M.gguf
sha256: dbaf619312e706c5440214d324d8f304717866675fc9728e3901c75ef5bbfeca
uri: huggingface://bartowski/Llama-3.1-WhiteRabbitNeo-2-8B-GGUF/Llama-3.1-WhiteRabbitNeo-2-8B-Q4_K_M.gguf
+- !!merge <<: *llama31
+ name: "tess-r1-limerick-llama-3.1-70b"
+ icon: https://huggingface.co/migtissera/Tess-R1-Llama-3.1-70B/resolve/main/Tess-R1-2.jpg
+ urls:
+ - https://huggingface.co/migtissera/Tess-R1-Limerick-Llama-3.1-70B
+ - https://huggingface.co/bartowski/Tess-R1-Limerick-Llama-3.1-70B-GGUF
+ description: |
+ Welcome to the Tess-Reasoning-1 (Tess-R1) series of models. Tess-R1 is designed with test-time compute in mind, and has the capabilities to produce a Chain-of-Thought (CoT) reasoning before producing the final output.
+
+ The model is trained to first think step-by-step, and contemplate on its answers. It can also write alternatives after contemplating. Once all the steps have been thought through, it writes the final output.
+
+ Step-by-step, Chain-of-Thought thinking process. Uses tags to indicate when the model is performing CoT.
+ tags are used when the model contemplate on its answers.
+ tags are used for alternate suggestions.
+ Finally, tags are used for the final output
+
+ Important Note:
+
+ In a multi-turn conversation, only the contents between the tags (discarding the tags) should be carried forward. Otherwise the model will see out of distribution input data and will fail.
+
+ The model was trained mostly with Chain-of-Thought reasoning data, including the XML tags. However, to generalize model generations, some single-turn and multi-turn data without XML tags were also included. Due to this, in some instances the model does not produce XML tags and does not fully utilize test-time compute capabilities. There is two ways to get around this:
+
+ Include a try/catch statement in your inference script, and only pass on the contents between the tags if it's available.
+ Use the tag as the seed in the generation, and force the model to produce outputs with XML tags. i.e: f"{conversation}{user_input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
+ overrides:
+ parameters:
+ model: Tess-R1-Limerick-Llama-3.1-70B-Q4_K_M.gguf
+ files:
+ - filename: Tess-R1-Limerick-Llama-3.1-70B-Q4_K_M.gguf
+ sha256: 92da5dad8a36ed5060becf78a83537d776079b7eaa4de73733d3ca57156286ab
+ uri: huggingface://bartowski/Tess-R1-Limerick-Llama-3.1-70B-GGUF/Tess-R1-Limerick-Llama-3.1-70B-Q4_K_M.gguf
- &deepseek
## Deepseek
url: "github:mudler/LocalAI/gallery/deepseek.yaml@master"