Merge pull request #1 from pppppM/eco-train

[Docs] Add Llama-Factory and Swift examples

ecosystem/README.md

@@ -24,10 +24,24 @@ You can find the best practice of finetuing the internlm2 model in the [README](
 
 LLaMA-Factory is an open-source, easy-to-use fine-tuning and training framework for LLMs
 
+```bash
+llamafactory-cli train \
+    --model_name_or_path internlm/internlm2-chat-1_8b \
+    --quantization_bit 4 --stage sft  --lora_target all \
+    --dataset 'identity,alpaca_en_demo' --template intern2 \
+    --output_dir output --do_train
+```
+
 ### [swift](https://github.com/modelscope/swift)
 
 SWIFT supports training, inference, evaluation and deployment of LLMs and MLLMs (multimodal large models).
 
+```bash
+swift sft --model_type internlm2-1_8b-chat \
+    --model_id_or_path Shanghai_AI_Laboratory/internlm2-chat-1_8b  \
+    --dataset AI-ModelScope/blossom-math-v2 --output_dir output
+```
+
 ## Inference
 
 ### [LMDeploy](https://github.com/InternLM/lmdeploy)

ecosystem/README_zh-CN.md

@@ -24,8 +24,22 @@ XTuner 是一个高效、灵活、全能的轻量化大模型微调工具库。
 
 LLaMA-Factory 是一个开源的、易于使用的 LLMs 微调和训练框架。
 
+```bash
+llamafactory-cli train \
+    --model_name_or_path internlm/internlm2-chat-1_8b \
+    --quantization_bit 4 --stage sft  --lora_target all \
+    --dataset 'identity,alpaca_en_demo' --template intern2 \
+    --output_dir output --do_train
+```
+
 ### [swift](https://github.com/modelscope/swift)
 
+```bash
+swift sft --model_type internlm2-1_8b-chat \
+    --model_id_or_path Shanghai_AI_Laboratory/internlm2-chat-1_8b  \
+    --dataset AI-ModelScope/blossom-math-v2 --output_dir output
+```
+
 SWIFT 支持 LLMs 和多模态大型模型（MLLMs）的训练、推理、评估和部署。
 
 ## 推理