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README.md

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+---
+language:
+- en
+- zh
+library_name: transformers
+tags:
+- Long Context
+- chatglm
+- llama
+datasets:
+- THUDM/LongWriter-6k
+---
+# LongWriter-glm4-9b
+
+<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/" target="_blank">[LongWriter Paper]</a> 
+</p>
+
+LongWriter-glm4-9b is trained based on [glm-4-9b-chat-1m](https://huggingface.co/THUDM/glm-4-9b-chat-1m), and is capable of generating 10,000+ words at once.
+
+
+A simple demo for deployment of the model:
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+tokenizer = AutoTokenizer.from_pretrained("THUDM/LongWriter-glm4-9b", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("THUDM/LongWriter-glm4-9b", 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)
+```
+
+## Citation
+
+If you find our work useful, please consider citing LongWriter:
+
+```
+
+```