chore(model gallery): add e-n-v-y_legion-v2.1-llama-70b-elarablated-v0.8-hf

gallery/index.yaml

@@ -988,7 +988,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -1006,7 +1006,7 @@
   description: |
     google/gemma-3-12b-it is an open-source, state-of-the-art, lightweight, multimodal model built from the same research and technology used to create the Gemini models. It is capable of handling text and image input and generating text output. It has a large context window of 128K tokens and supports over 140 languages. The 12B variant has been fine-tuned using the instruction-tuning approach. Gemma 3 models are suitable for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes them deployable in environments with limited resources such as laptops, desktops, or your own cloud infrastructure.
   overrides:
     #mmproj: gemma-3-12b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-12b-it-Q4_K_M.gguf
   files:
@@ -1024,7 +1024,7 @@
   description: |
     Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma 3 models are multimodal, handling text and image input and generating text output, with open weights for both pre-trained variants and instruction-tuned variants. Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. Gemma-3-4b-it is a 4 billion parameter model.
   overrides:
     #mmproj: gemma-3-4b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-4b-it-Q4_K_M.gguf
   files:
@@ -2880,6 +2880,28 @@
     - filename: TheDrummer_Valkyrie-49B-v1-Q4_K_M.gguf
       sha256: f50be1eef41e0da2cb59e4b238f4f178ee1000833270b337f97f91572c31b752
       uri: huggingface://bartowski/TheDrummer_Valkyrie-49B-v1-GGUF/TheDrummer_Valkyrie-49B-v1-Q4_K_M.gguf
+- !!merge <<: *llama33
+  name: "e-n-v-y_legion-v2.1-llama-70b-elarablated-v0.8-hf"
+  urls:
+    - https://huggingface.co/e-n-v-y/Legion-V2.1-LLaMa-70B-Elarablated-v0.8-hf
+    - https://huggingface.co/bartowski/e-n-v-y_Legion-V2.1-LLaMa-70B-Elarablated-v0.8-hf-GGUF
+  description: |
+    This checkpoint was finetuned with a process I'm calling "Elarablation" (a portamenteau of "Elara", which is a name that shows up in AI-generated writing and RP all the time) and "ablation". The idea is to reduce the amount of repetitiveness and "slop" that the model exhibits. In addition to significantly reducing the occurrence of the name "Elara", I've also reduced other very common names that pop up in certain situations. I've also specifically attacked two phrases, "voice barely above a whisper" and "eyes glinted with mischief", which come up a lot less often now. Finally, I've convinced it that it can put a f-cking period after the word "said" because a lot of slop-ish phrases tend to come after "said,".
+
+    You can check out some of the more technical details in the overview on my github repo, here:
+
+    https://github.com/envy-ai/elarablate
+
+    My current focus has been on some of the absolute worst offending phrases in AI creative writing, but I plan to go after RP slop as well. If you run into any issues with this model (going off the rails, repeating tokens, etc), go to the community tab and post the context and parameters in a comment so I can look into it. Also, if you have any "slop" pet peeves, post the context of those as well and I can try to reduce/eliminate them in the next version.
+
+    The settings I've tested with are temperature at 0.7 and all other filters completely neutral. Other settings may lead to better or worse results.
+  overrides:
+    parameters:
+      model: e-n-v-y_Legion-V2.1-LLaMa-70B-Elarablated-v0.8-hf-Q4_K_M.gguf
+  files:
+    - filename: e-n-v-y_Legion-V2.1-LLaMa-70B-Elarablated-v0.8-hf-Q4_K_M.gguf
+      sha256: 2d57b5b0788761f3adb54b60f0e3dcf43a7b2e5bd83c475c689f7f86e86bbc90
+      uri: huggingface://bartowski/e-n-v-y_Legion-V2.1-LLaMa-70B-Elarablated-v0.8-hf-GGUF/e-n-v-y_Legion-V2.1-LLaMa-70B-Elarablated-v0.8-hf-Q4_K_M.gguf
 - &rwkv
   url: "github:mudler/LocalAI/gallery/rwkv.yaml@master"
   name: "rwkv-6-world-7b"
@@ -4057,7 +4079,7 @@
       sha256: b9f01bead9e163db9351af036d8d63ef479d7d48a1bb44934ead732a180f371c
       uri: huggingface://bartowski/Menlo_ReZero-v0.1-llama-3.2-3b-it-grpo-250404-GGUF/Menlo_ReZero-v0.1-llama-3.2-3b-it-grpo-250404-Q4_K_M.gguf
 - &qwen25
   name: "qwen2.5-14b-instruct" ## Qwen2.5
   icon: https://avatars.githubusercontent.com/u/141221163
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
   license: apache-2.0
@@ -6018,7 +6040,7 @@
       sha256: 0fec82625f74a9a340837de7af287b1d9042e5aeb70cda2621426db99958b0af
       uri: huggingface://bartowski/Chuluun-Qwen2.5-72B-v0.08-GGUF/Chuluun-Qwen2.5-72B-v0.08-Q4_K_M.gguf
 - &smollm
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master" ## SmolLM
   name: "smollm-1.7b-instruct"
   icon: https://huggingface.co/datasets/HuggingFaceTB/images/resolve/main/banner_smol.png
   tags:
@@ -7719,7 +7741,7 @@
       sha256: 4a7bc5478a2ec8c5d186d63532eb22e75b79ba75ec3c0ce821676157318ef4ad
       uri: https://huggingface.co/ggml-org/Qwen2.5-Omni-7B-GGUF/resolve/main/mmproj-Qwen2.5-Omni-7B-Q8_0.gguf
 - &llama31
   url: "github:mudler/LocalAI/gallery/llama3.1-instruct.yaml@master" ## LLama3.1
   icon: https://avatars.githubusercontent.com/u/153379578
   name: "meta-llama-3.1-8b-instruct"
   license: llama3.1