初始化项目，由ModelHub XC社区提供模型

Model: zai-org/LongWriter-llama3.1-8b
Source: Original Platform

README.md

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+---
+language:
+- en
+- zh
+library_name: transformers
+tags:
+- Long Context
+- chatglm
+- llama
+datasets:
+- THUDM/LongWriter-6k
+license: llama3.1
+---
+# LongWriter-llama3.1-8b
+
+<p align="center">
+  🤗 <a href="https://huggingface.co/datasets/THUDM/LongWriter-6k" target="_blank">[LongWriter Dataset] </a> • 💻 <a href="https://github.com/THUDM/LongWriter" target="_blank">[Github Repo]</a> • 📃 <a href="https://arxiv.org/abs/2408.07055" target="_blank">[LongWriter Paper]</a> 
+</p>
+
+LongWriter-llama3.1-8b is trained based on [Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B), and is capable of generating 10,000+ words at once.
+
+Environment: `transformers>=4.43.0`
+
+Please ahere to the prompt template (system prompt is optional): `<<SYS>>\n{system prompt}\n<</SYS>>\n\n[INST]{query1}[/INST]{response1}[INST]{query2}[/INST]{response2}...`
+
+A simple demo for deployment of the model:
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+tokenizer = AutoTokenizer.from_pretrained("THUDM/LongWriter-llama3.1-8b", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("THUDM/LongWriter-llama3.1-8b", torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")
+model = model.eval()
+query = "Write a 10000-word China travel guide"
+prompt = f"[INST]{query}[/INST]"
+input = tokenizer(prompt, truncation=False, return_tensors="pt").to(device)
+context_length = input.input_ids.shape[-1]
+output = model.generate(
+    **input,
+    max_new_tokens=32768,
+    num_beams=1,
+    do_sample=True,
+    temperature=0.5,
+)[0]
+response = tokenizer.decode(output[context_length:], skip_special_tokens=True)
+print(response)
+```
+You can also deploy the model with [vllm](https://github.com/vllm-project/vllm), which allows 10,000+ words generation within a minute. Here is an example code:
+```python
+model = LLM(
+    model= "THUDM/LongWriter-llama3.1-8b",
+    dtype="auto",
+    trust_remote_code=True,
+    tensor_parallel_size=1,
+    max_model_len=32768,
+    gpu_memory_utilization=0.5,
+)
+tokenizer = model.get_tokenizer()
+generation_params = SamplingParams(
+    temperature=0.5,
+    top_p=0.8,
+    top_k=50,
+    max_tokens=32768,
+    repetition_penalty=1,
+)
+query = "Write a 10000-word China travel guide"
+prompt = f"[INST]{query}[/INST]"
+input_ids = tokenizer(prompt, truncation=False, return_tensors="pt").input_ids[0].tolist()
+outputs = model.generate(
+    sampling_params=generation_params,
+    prompt_token_ids=[input_ids],
+)
+output = outputs[0]
+print(output.outputs[0].text)
+```
+
+License: [Llama-3.1 License](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B/blob/main/LICENSE)
+
+## Citation
+
+If you find our work useful, please consider citing LongWriter:
+
+```
+@article{bai2024longwriter,
+  title={LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs}, 
+  author={Yushi Bai and Jiajie Zhang and Xin Lv and Linzhi Zheng and Siqi Zhu and Lei Hou and Yuxiao Dong and Jie Tang and Juanzi Li},
+  journal={arXiv preprint arXiv:2408.07055},
+  year={2024}
+}
+```