Update train.mdx with Wandb configuration and requirements

- Added detailed requirements for training, including Huggingface token and model details
- Included Wandb login and configuration instructions
- Updated documentation with environment variables for Wandb logging

docs/train.mdx

@@ -28,8 +28,11 @@ praisonai train init
 
 ## Required
 
-1. HF_TOKEN
-2. Below config.yaml file in the same directory
+1. Huggingface token
+2. Base model to train on (e.g. unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit)
+3. Dataset to train on (e.g. yahma/alpaca-cleaned)
+4. Huggingface model name to upload to (e.g. mervinpraison/llama3.1-instruct) (Optional)
+5. Ollama model name to upload to (e.g. mervinpraison/llama3.1-instruct) (Optional)
 
 ## To upload to ollama.com (Linux)
 
@@ -119,4 +122,21 @@ quantization_method:
 
 ```bash
 praisonai train
+```
+
+## wandb
+
+```bash
+wandb login
+```
+
+<Note>
+Get the key from [here](https://wandb.ai/site/login)
+</Note>
+
+```bash
+export PRAISON_WANDB=True
+export WANDB_LOG_MODEL=checkpoint
+export WANDB_PROJECT=praisonai-test
+export PRAISON_WANDB_RUN_NAME=praisonai-train  
 ```

praisonai/setup/setup_conda_env.sh

@@ -100,6 +100,6 @@ $PIP_FULL_PATH install "unsloth[colab-new] @ git+https://github.com/unslothai/un
 $PIP_FULL_PATH install --no-deps "trl<0.9.0" peft accelerate bitsandbytes 
 $PIP_FULL_PATH install unsloth_zoo
 $PIP_FULL_PATH install cut_cross_entropy
-$PIP_FULL_PATH install sentencepiece protobuf datasets huggingface_hub hf_transfer
+$PIP_FULL_PATH install sentencepiece protobuf datasets huggingface_hub hf_transfer wandb
 
 echo "Setup completed successfully!"