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README.md

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+---
+base_model: mzbac/Phi-3-mini-4k-grammar-correction
+inference: true
+license: mit
+model_creator: mzbac
+model_name: Phi-3-mini-4k-grammar-correction
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- gguf
+- ggml
+- quantized
+---
+
+# Phi-3-mini-4k-grammar-correction-GGUF
+
+Quantized GGUF model files for [Phi-3-mini-4k-grammar-correction](https://huggingface.co/mzbac/Phi-3-mini-4k-grammar-correction) from [mzbac](https://huggingface.co/mzbac)
+
+## Original Model Card:
+
+# Usage
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "mzbac/Phi-3-mini-4k-grammar-correction"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+messages = [
+    {
+        "role": "user",
+        "content": "Please correct, polish, or translate the text delimited by triple backticks to standard English.",
+    },
+    {
+        "role": "user",
+        "content": "Text=```neither 经理或员工 has been informed about the meeting```",
+    },
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages, add_generation_prompt=True, return_tensors="pt"
+).to(model.device)
+
+terminators = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids("<|end|>")]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.1,
+)
+response = outputs[0]
+print(tokenizer.decode(response))
+
+# <s><|user|> Please correct, polish, or translate the text delimited by triple backticks to standard English.<|end|><|assistant|>
+# <|user|> Text=```neither 经理或员工 has been informed about the meeting```<|end|>
+# <|assistant|> Output=Neither the manager nor the employee has been informed about the meeting.<|end|>
+```