Upload folder using huggingface_hub

README.md

@@ -0,0 +1,84 @@
+---
+base_model:
+- mistralai/Mistral-7B-Instruct-v0.3
+- uukuguy/speechless-code-mistral-7b-v2.0
+- Nondzu/Mistral-7B-Instruct-v0.2-code-ft
+- teknium/OpenHermes-2.5-Mistral-7B
+- meta-math/MetaMath-Mistral-7B
+tags:
+- merge
+- mergekit
+- lazymergekit
+- mistralai/Mistral-7B-Instruct-v0.3
+- uukuguy/speechless-code-mistral-7b-v2.0
+- Nondzu/Mistral-7B-Instruct-v0.2-code-ft
+- teknium/OpenHermes-2.5-Mistral-7B
+- meta-math/MetaMath-Mistral-7B
+---
+
+# Mistral-CodingBeast-7B
+
+Mistral-CodingBeast-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3)
+* [uukuguy/speechless-code-mistral-7b-v2.0](https://huggingface.co/uukuguy/speechless-code-mistral-7b-v2.0)
+* [Nondzu/Mistral-7B-Instruct-v0.2-code-ft](https://huggingface.co/Nondzu/Mistral-7B-Instruct-v0.2-code-ft)
+* [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
+* [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
+
+## 🧩 Configuration
+
+```yaml
+merge_method: dare_ties
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+models:
+  - model: mistralai/Mistral-7B-Instruct-v0.3
+    parameters:
+      weight: 0.15
+      density: 0.5
+  - model: uukuguy/speechless-code-mistral-7b-v2.0
+    parameters:
+      weight: 0.25
+      density: 0.7
+  - model: Nondzu/Mistral-7B-Instruct-v0.2-code-ft
+    parameters:
+      weight: 0.2
+      density: 0.6
+  - model: teknium/OpenHermes-2.5-Mistral-7B
+    parameters:
+      weight: 0.2
+      density: 0.6
+  - model: meta-math/MetaMath-Mistral-7B
+    parameters:
+      weight: 0.2
+      density: 0.6
+parameters:
+  int8_mask: true
+  normalize: true
+dtype: bfloat16
+tokenizer_source: mistralai/Mistral-7B-Instruct-v0.3
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "AIencoder/Mistral-CodingBeast-7B"
+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"])
+```