初始化项目，由ModelHub XC社区提供模型

Model: MaziyarPanahi/Yarn-Mistral-7b-64k-Mistral-7B-Instruct-v0.1
Source: Original Platform

README.md

@@ -0,0 +1,80 @@
+---
+license: apache-2.0
+tags:
+- Safetensors
+- mistral
+- text-generation-inference
+- merge
+- mistral
+- 7b
+- mistralai/Mistral-7B-Instruct-v0.1
+- NousResearch/Yarn-Mistral-7b-64k
+- transformers
+- pytorch
+- mistral
+- text-generation
+- custom_code
+- en
+- dataset:emozilla/yarn-train-tokenized-16k-mistral
+- arxiv:2309.00071
+- license:apache-2.0
+- autotrain_compatible
+- endpoints_compatible
+- has_space
+- text-generation-inference
+- region:us
+---
+
+# Yarn-Mistral-7b-64k-Mistral-7B-Instruct-v0.1
+
+Yarn-Mistral-7b-64k-Mistral-7B-Instruct-v0.1 is a merge of the following models:
+* [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
+* [NousResearch/Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: mistralai/Mistral-7B-Instruct-v0.1
+        layer_range: [0, 32]
+      - model: NousResearch/Yarn-Mistral-7b-64k
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: mistralai/Mistral-7B-Instruct-v0.1
+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 = "MaziyarPanahi/Yarn-Mistral-7b-64k-Mistral-7B-Instruct-v0.1"
+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"])
+```