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"