Create README.md

README.md

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+---
+language:
+- zh
+thumbnail: >-
+ https://s3.amazonaws.com/moonup/production/uploads/1677459920577-63b8e3432adad59f41dc65f4.jpeg?w=200&h=200&f=face
+tags:
+- bloom
+license: bigscience-bloom-rail-1.0
+pipeline_tag: text-generation
+widget:
+- text:问:真昼是谁?\n答:
+---
+
+# Bloom 7B1 LightNovel ZH_CN LoRa Finetuned
+
+
+BigScience Large Open-science Open-access Multilingual Language Model with 7,1 billion parameters finetuned on Chinese Translation of Japanese LightNovel using LoRa from PEFT (?)
+
+## Model Details
+
+I just downloaded 50 LightNovels then finetuned the model on raw text.
+
+Trained by Rorical
+
+## Use
+
+```python
+import torch
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+peft_model_id = "Rorical/bloom-7b1-lightnovel-lora"
+config = PeftConfig.from_pretrained(peft_model_id)
+model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='auto', cache_dir="cache")
+tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path, cache_dir="cache")
+model = PeftModel.from_pretrained(model, peft_model_id, cache_dir="cache")
+
+prompt = "你是谁？\n"
+batch = tokenizer(prompt, return_tensors='pt').to("cuda")
+
+with torch.cuda.amp.autocast():
+ output_tokens = model.generate(**batch, max_new_tokens=150, do_sample=True, top_k=50, top_p=0.95)
+
+print(tokenizer.decode(output_tokens[0], skip_special_tokens=True))
+```