Update README.md

README.md

@@ -15,6 +15,59 @@ base_model: anthracite-org/magnum-v4-9b
 This model was converted to GGUF format from [`anthracite-org/magnum-v4-9b`](https://huggingface.co/anthracite-org/magnum-v4-9b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/anthracite-org/magnum-v4-9b) for more details on the model.
 
+---
+This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus.
+
+This model is fine-tuned on top of gemma 2 9b (chatML'ified).
+Prompting
+
+A typical input would look like this:
+
+<|im_start|>system
+system prompt<|im_end|>
+<|im_start|>user
+Hi there!<|im_end|>
+<|im_start|>assistant
+Nice to meet you!<|im_end|>
+<|im_start|>user
+Can I ask a question?<|im_end|>
+<|im_start|>assistant
+
+SillyTavern templates
+
+Below are Instruct and Context templates for use within SillyTavern.
+context template
+
+
+instruct template
+
+
+Axolotl config
+See axolotl config
+
+
+Credits
+
+We'd like to thank Recursal / Featherless for sponsoring the compute for this train, Featherless has been hosting our Magnum models since the first 72 B and has given thousands of people access to our models and helped us grow.
+
+We would also like to thank all members of Anthracite who made this finetune possible.
+Datasets
+
+    anthracite-org/c2_logs_16k_llama_v1.1
+    NewEden/Claude-Instruct-5K
+    anthracite-org/kalo-opus-instruct-22k-no-refusal
+    Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
+    lodrick-the-lafted/kalo-opus-instruct-3k-filtered
+    anthracite-org/nopm_claude_writing_fixed
+    Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
+    anthracite-org/kalo_opus_misc_240827
+    anthracite-org/kalo_misc_part2
+
+Training
+
+The training was done for 2 epochs. We used 8xH100s GPUs graciously provided by Recursal AI / Featherless AI for the full-parameter fine-tuning of the model.
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)