Upload folder using huggingface_hub

README.md

@@ -0,0 +1,67 @@
+---
+{}
+---
+---
+    license: apache-2.0
+    base_model:
+      - OpenPipe/mistral-ft-optimized-1218
+      - mlabonne/NeuralHermes-2.5-Mistral-7B
+    tags:
+      - merge
+      - mergekit
+      - lazymergekit
+      - OpenPipe/mistral-ft-optimized-1218
+      - mlabonne/NeuralHermes-2.5-Mistral-7B
+    ---
+
+    # NeuralPipe-7B-slerp
+    NeuralPipe-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+    * [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/%7B%7B%20model%20%7D%7D)
+    * [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/%7B%7B%20model%20%7D%7D)
+
+    ## 🧩 Configuration
+
+    ```yaml
+slices:
+  - sources:
+      - model: OpenPipe/mistral-ft-optimized-1218
+        layer_range: [0, 32]
+      - model: mlabonne/NeuralHermes-2.5-Mistral-7B
+        layer_range: [0, 32]
+  - merge_method: slerp
+    base_model: OpenPipe/mistral-ft-optimized-1218
+    parameters:
+      t:
+        - filter: self_attn
+          value: [0, 0.5, 0.3, 0.7, 1]
+        - filter: mlp
+          value: [1, 0.5, 0.7, 0.3, 0]
+        - value: 0.5
+    dtype: bfloat16
+```
+
+    ## 💻 Usage
+
+    ```python
+    !pip install -qU transformers accelerate
+
+    from transformers import AutoTokenizer
+    import transformers
+    import torch
+
+    model = "shism/NeuralPipe-7B-slerp"
+    messages = [{"role": "user", "content": "What is a large language model?"}]
+
+    tokenizer = AutoTokenizer.from_pretrained(model)
+    prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+    pipeline = transformers.pipeline(
+        "text-generation",
+        model=model,
+        torch_dtype=torch.float16,
+        device_map="auto",
+    )
+
+    outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+    print(outputs[0]["generated_text"])
+    ```