Update README.md

README.md

@@ -1,14 +1,55 @@
 ---
-base_model: cognitivecomputations/mixtral-1x22b-base
+license: apache-2.0
+base_model: mistral-community/Mixtral-8x22B-v0.1
 tags:
 - generated_from_trainer
+- axolotl
 model-index:
-- name: 1x22b-out
+- name: out
   results: []
+datasets:
+- cognitivecomputations/Dolphin-2.9
+- teknium/OpenHermes-2.5
+- m-a-p/CodeFeedback-Filtered-Instruction
+- cognitivecomputations/dolphin-coder
+- cognitivecomputations/samantha-data
+- microsoft/orca-math-word-problems-200k
+- abacusai/SystemChat-1.1
+- Locutusque/function-calling-chatml
+- internlm/Agent-FLAN
+language:
+- en
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Dolphin 2.9 Mixtral 8x22b 🐬
+
+Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
+
+[![Discord](https://img.shields.io/discord/1156064224225808488?logo=Discord&logoColor=%23ffffff&label=Discord&link=https%3A%2F%2Fdiscord.gg%2FtCMkMDDHwm)](https://discord.gg/cognitivecomputations)
+Discord: https://discord.gg/cognitivecomputations
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
+
+This model is based on Dolphin-2.9-Mixtral-8x22b, and is Apache-2.0 licensed.
+
+The base model has 64k context, and the full-weight fine-tuning was with 16k sequence length.
+
+It took 27 hours on 8xH100 provided by Crusoe Cloud.
+
+This model was fully fine-tuned, targeting all layers.
+
+The model is an extracted expert using SLERP and a custom script that we've open-sourced (I'll provide the link to the GitHub). It extracts a single expert which is the combined SLERP of all 8 experts from a Mixtral architecture. We decided to not fully convert to a dense model, for the sake of trying to keep as much of the original model's performance as possible, as this process is already quite surgical and there are a lot of variables to take into account.
+
+Dolphin-2.9 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
+
+Dolphin is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
+
+Dolphin is licensed Apache 2.0. I grant permission for any use, including commercial, that falls within accordance with Apache-2.0 license. Dolphin was trained on data generated from GPT4, among other models.
+
+## Evals
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/Nb6f_dS_M6fN_v2ACK98x.png)
+
 
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
 <details><summary>See axolotl config</summary>
@@ -380,10 +421,6 @@ tokens:
 
 # 1x22b-out
 
-This model is a fine-tuned version of [cognitivecomputations/mixtral-1x22b-base](https://huggingface.co/cognitivecomputations/mixtral-1x22b-base) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4572
-
 ## Model description
 
 More information needed