Cloud Merging (#410)

Introduces a light cloud merging option from Arcee

README.md

@@ -11,10 +11,10 @@ Features:
 - Interpolated gradients for parameter values (inspired by Gryphe's [BlockMerge_Gradient](https://github.com/Gryphe/BlockMerge_Gradient) script)
 - Piecewise assembly of language models from layers ("Frankenmerging")
 - [Mixture of Experts merging](#mixture-of-experts-merging)
+- [LORA extraction](#lora-extraction)
+- [Evolutionary merge methods](#evolutionary-merge-methods)
 
-🔊 Call to Evolve - to solve evolutionary merge methods as a community - please see <https://github.com/arcee-ai/mergekit/issues/207>.
-
-🌐 GUI Launch Alert 🤗 - We are excited to announce the launch of a graphical user interface for mergekit in Hugging Face Spaces! This GUI simplifies the merging process, making it more accessible to a broader audience. Check it out and contribute at [Hugging Face Spaces - mergekit-community](https://huggingface.co/mergekit-community).
+🌐 GUI Launch Alert 🤗 - We are excited to announce the launch of a mega-GPU Backed graphical user interface for mergekit in Arcee! This GUI simplifies the merging process, making it more accessible to a broader audience. Check it out and contribute at the [Arcee App](app.arcee.ai). There is also a [Hugging Face Space](https://huggingface.co/mergekit-community) with limited amounts of GPUs.
 
 ## Installation
 
@@ -213,6 +213,35 @@ mergekit-extract-lora finetuned_model_id_or_path base_model_id_or_path output_pa
 
 The `mergekit-moe` script supports merging multiple dense models into a mixture of experts, either for direct use or for further training. For more details see the [`mergekit-moe` documentation](docs/moe.md).
 
+## Evolutionary merge methods
+
+See `docs/evolve.md` for details.
+
+## ✨ Merge in the Cloud ✨
+
+We host merging on Arcee's cloud GPUs - you can launch a cloud merge in the [Arcee App](app.arcee.ai). Or through python - grab an ARCEE_API_KEY:
+
+`export ARCEE_API_KEY=<your-api-key>`
+`pip install -q arcee-py`
+
+```
+import arcee
+arcee.merge_yaml("bio-merge","./examples/bio-merge.yml")
+```
+
+Check your merge status at the [Arcee App](app.arcee.ai)
+
+When complete, either deploy your merge:
+
+```
+arcee.start_deployment("bio-merge", merging="bio-merge")
+```
+
+Or download your merge:
+
+`!arcee merging download bio-merge`
+
+
 ## Citation
 
 We now have a [paper](https://arxiv.org/abs/2403.13257) you can cite for the MergeKit library:

examples/bio-merge.yml

@@ -0,0 +1,15 @@
+models:
+  - model: mistralai/Mistral-7B-Instruct-v0.2
+    parameters:
+      density: 0.5
+      weight: 0.5
+  - model: BioMistral/BioMistral-7B
+    parameters:
+      density: 0.5
+      weight: 0.5
+merge_method: ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  normalize: false
+  int8_mask: true
+dtype: float16