Delete docs/transformers_deploy_guide.md with huggingface_hub

docs/transformers_deploy_guide.md

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-# MiniMax M2.1 Model Transformers Deployment Guide
-
-[English Version](./transformers_deploy_guide.md) | [Chinese Version](./transformers_deploy_guide_cn.md)
-
-## Applicable Models
-
-This document applies to the following models. You only need to change the model name during deployment.
-
-- [MiniMaxAI/MiniMax-M2.1](https://huggingface.co/MiniMaxAI/MiniMax-M2.1)
-- [MiniMaxAI/MiniMax-M2](https://huggingface.co/MiniMaxAI/MiniMax-M2)
-
-The deployment process is illustrated below using MiniMax-M2.1 as an example.
-
-## System Requirements
-
-- OS: Linux
-
-- Python: 3.9 - 3.12
-
-- Transformers: 4.57.1
-
-- GPU:
-
-  - compute capability 7.0 or higher
-
-  - Memory requirements: 220 GB for weights.
-
-## Deployment with Python
-
-It is recommended to use a virtual environment (such as **venv**, **conda**, or **uv**) to avoid dependency conflicts. 
-
-We recommend installing Transformers in a fresh Python environment:
-
-```bash
-uv pip install transformers==4.57.1 torch accelerate --torch-backend=auto
-```
-
-Run the following Python script to run the model. Transformers will automatically download and cache the MiniMax-M2.1 model from Hugging Face.
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
-import torch
-
-MODEL_PATH = "MiniMaxAI/MiniMax-M2.1"
-
-model = AutoModelForCausalLM.from_pretrained(
-    MODEL_PATH,
-    device_map="auto",
-    trust_remote_code=True,
-)
-tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
-
-messages = [
-    {"role": "user", "content": [{"type": "text", "text": "What is your favourite condiment?"}]},
-    {"role": "assistant", "content": [{"type": "text", "text": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"}]},
-    {"role": "user", "content": [{"type": "text", "text": "Do you have mayonnaise recipes?"}]}
-]
-
-model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to("cuda")
-
-generated_ids = model.generate(model_inputs, max_new_tokens=100, generation_config=model.generation_config)
-
-response = tokenizer.batch_decode(generated_ids)[0]
-
-print(response)
-```
-
-## Common Issues
-
-### Hugging Face Network Issues
-
-If you encounter network issues, you can set up a proxy before pulling the model.
-
-```bash
-export HF_ENDPOINT=https://hf-mirror.com
-```
-
-### MiniMax-M2 model is not currently supported
-
-Please check that trust_remote_code=True.
-
-## Getting Support
-
-If you encounter any issues while deploying the MiniMax model:
-
-- Contact our technical support team through official channels such as email at [model@minimax.io](mailto:model@minimax.io)
-
-- Submit an issue on our [GitHub](https://github.com/MiniMax-AI) repository
-
-We continuously optimize the deployment experience for our models. Feedback is welcome!
-