remove LICENSE and fix README

.runpod/LICENSE

@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2023 runpod-workers
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.

.runpod/README.md

@@ -1,15 +1,5 @@
-
-
 <h1>LLM Training- Full finetune, LoRA, QLoRa etc. Llama/Mistral/Gemma</h1>
 
-## RunPod Worker Images
-
-Below is a summary of the available RunPod Worker images, categorized by image stability and CUDA version compatibility.
-
-| Preview Image Tag                  | Development Image Tag             |
------------------------------------|-----------------------------------|
-| `runpod/llm-finetuning:preview` | `runpod/llm-finetuning:dev` 
-
 # Configuration Options
 
 This document outlines all available configuration options for training models. The configuration can be provided as a JSON request.
@@ -19,6 +9,7 @@ This document outlines all available configuration options for training models.
 You can use these configuration Options:
 
 1. As a JSON request body:
+
 ```json
 {
   "input": {
@@ -42,7 +33,7 @@ You can use these configuration Options:
 ### Model Configuration
 
 | Option              | Description                                                                                   | Default              |
-|--------|-------------|---------|
+| ------------------- | --------------------------------------------------------------------------------------------- | -------------------- |
 | `base_model`        | Path to the base model (local or HuggingFace)                                                 | Required             |
 | `base_model_config` | Configuration path for the base model                                                         | Same as base_model   |
 | `revision_of_model` | Specific model revision from HuggingFace hub                                                  | Latest               |
@@ -51,12 +42,10 @@ You can use these configuration Options:
 | `tokenizer_type`    | Type of tokenizer to use                                                                      | AutoTokenizer        |
 | `hub_model_id`      | Repository ID where the model will be pushed on Hugging Face Hub (format: username/repo-name) | Optional             |
 
-
-
 ## Model Family Identification
 
 | Option                     | Default | Description                    |
-|--------|---------|-------------|
+| -------------------------- | ------- | ------------------------------ |
 | `is_falcon_derived_model`  | `false` | Whether model is Falcon-based  |
 | `is_llama_derived_model`   | `false` | Whether model is LLaMA-based   |
 | `is_qwen_derived_model`    | `false` | Whether model is Qwen-based    |
@@ -65,25 +54,24 @@ You can use these configuration Options:
 ## Model Configuration Overrides
 
 | Option                                          | Default    | Description                        |
-|--------|---------|-------------|
+| ----------------------------------------------- | ---------- | ---------------------------------- |
 | `overrides_of_model_config.rope_scaling.type`   | `"linear"` | RoPE scaling type (linear/dynamic) |
 | `overrides_of_model_config.rope_scaling.factor` | `1.0`      | RoPE scaling factor                |
 
 ### Model Loading Options
 
 | Option         | Description                   | Default |
-|--------|-------------|---------|
+| -------------- | ----------------------------- | ------- |
 | `load_in_8bit` | Load model in 8-bit precision | false   |
 | `load_in_4bit` | Load model in 4-bit precision | false   |
 | `bf16`         | Use bfloat16 precision        | false   |
 | `fp16`         | Use float16 precision         | false   |
 | `tf32`         | Use tensor float 32 precision | false   |
 
-
 ## Memory and Device Settings
 
 | Option             | Default   | Description             |
-|--------|---------|-------------|
+| ------------------ | --------- | ----------------------- |
 | `gpu_memory_limit` | `"20GiB"` | GPU memory limit        |
 | `lora_on_cpu`      | `false`   | Load LoRA on CPU        |
 | `device_map`       | `"auto"`  | Device mapping strategy |
@@ -92,7 +80,7 @@ You can use these configuration Options:
 ## Training Hyperparameters
 
 | Option                        | Default   | Description                 |
-|--------|---------|-------------|
+| ----------------------------- | --------- | --------------------------- |
 | `gradient_accumulation_steps` | `1`       | Gradient accumulation steps |
 | `micro_batch_size`            | `2`       | Batch size per GPU          |
 | `eval_batch_size`             | `null`    | Evaluation batch size       |
@@ -121,11 +109,10 @@ datasets:
     train_on_split: train # Dataset split to use
 ```
 
-
 ## Chat Template Settings
 
 | Option                   | Default                          | Description            |
-|--------|---------|-------------|
+| ------------------------ | -------------------------------- | ---------------------- |
 | `chat_template`          | `"tokenizer_default"`            | Chat template type     |
 | `chat_template_jinja`    | `null`                           | Custom Jinja template  |
 | `default_system_message` | `"You are a helpful assistant."` | Default system message |
@@ -133,7 +120,7 @@ datasets:
 ## Dataset Processing
 
 | Option                        | Default                    | Description                       |
-|--------|---------|-------------|
+| ----------------------------- | -------------------------- | --------------------------------- |
 | `dataset_prepared_path`       | `"data/last_run_prepared"` | Path for prepared dataset         |
 | `push_dataset_to_hub`         | `""`                       | Push dataset to HF hub            |
 | `dataset_processes`           | `4`                        | Number of preprocessing processes |
@@ -144,7 +131,7 @@ datasets:
 ## LoRA Configuration
 
 | Option                     | Default                | Description                    |
-|--------|---------|-------------|
+| -------------------------- | ---------------------- | ------------------------------ |
 | `adapter`                  | `"lora"`               | Adapter type (lora/qlora)      |
 | `lora_model_dir`           | `""`                   | Directory with pretrained LoRA |
 | `lora_r`                   | `8`                    | LoRA attention dimension       |
@@ -156,11 +143,10 @@ datasets:
 | `lora_modules_to_save`     | `[]`                   | Modules to save                |
 | `lora_fan_in_fan_out`      | `false`                | Fan in/out structure           |
 
-
 ## Optimization Settings
 
 | Option                    | Default | Description                |
-|--------|---------|-------------|
+| ------------------------- | ------- | -------------------------- |
 | `train_on_inputs`         | `false` | Train on input prompts     |
 | `group_by_length`         | `false` | Group by sequence length   |
 | `gradient_checkpointing`  | `false` | Use gradient checkpointing |
@@ -169,7 +155,7 @@ datasets:
 ## Learning Rate Scheduling
 
 | Option                     | Default    | Description          |
-|--------|---------|-------------|
+| -------------------------- | ---------- | -------------------- |
 | `lr_scheduler`             | `"cosine"` | Scheduler type       |
 | `lr_scheduler_kwargs`      | `{}`       | Scheduler parameters |
 | `cosine_min_lr_ratio`      | `null`     | Minimum LR ratio     |
@@ -179,7 +165,7 @@ datasets:
 ## Optimizer Settings
 
 | Option                 | Default      | Description         |
-|--------|---------|-------------|
+| ---------------------- | ------------ | ------------------- |
 | `optimizer`            | `"adamw_hf"` | Optimizer choice    |
 | `optim_args`           | `{}`         | Optimizer arguments |
 | `optim_target_modules` | `[]`         | Target modules      |
@@ -192,7 +178,7 @@ datasets:
 ## Attention Implementations
 
 | Option                     | Default | Description                   |
-|--------|---------|-------------|
+| -------------------------- | ------- | ----------------------------- |
 | `flash_optimum`            | `false` | Use better transformers       |
 | `xformers_attention`       | `false` | Use xformers                  |
 | `flash_attention`          | `false` | Use flash attention           |
@@ -203,18 +189,17 @@ datasets:
 | `sdp_attention`            | `false` | Use scaled dot product        |
 | `s2_attention`             | `false` | Use shifted sparse attention  |
 
-
 ## Tokenizer Modifications
 
 | Option           | Default | Description                  |
-|--------|---------|-------------|
+| ---------------- | ------- | ---------------------------- |
 | `special_tokens` | -       | Special tokens to add/modify |
 | `tokens`         | `[]`    | Additional tokens            |
 
 ## Distributed Training
 
 | Option                  | Default | Description           |
-|--------|---------|-------------|
+| ----------------------- | ------- | --------------------- |
 | `fsdp`                  | `null`  | FSDP configuration    |
 | `fsdp_config`           | `null`  | FSDP config options   |
 | `deepspeed`             | `null`  | Deepspeed config path |
@@ -222,7 +207,6 @@ datasets:
 | `ddp_bucket_cap_mb`     | `null`  | DDP bucket capacity   |
 | `ddp_broadcast_buffers` | `null`  | DDP broadcast buffers |
 
-
 <details>
 <summary><h3>Example Configuration Request:</h3></summary>
 
@@ -299,20 +283,21 @@ Here's a complete example for fine-tuning a LLaMA model using LoRA:
   }
 }
 ```
+
 </details>
 
 ### Advanced Features
 
 #### Wandb Integration
+
 - `wandb_project`: Project name for Weights & Biases
 - `wandb_entity`: Team name in W&B
 - `wandb_watch`: Monitor model with W&B
 - `wandb_name`: Name of the W&B run
 - `wandb_run_id`: ID for the W&B run
 
-
-
 #### Performance Optimization
+
 - `sample_packing`: Enable efficient sequence packing
 - `eval_sample_packing`: Use sequence packing during evaluation
 - `torch_compile`: Enable PyTorch 2.0 compilation
@@ -336,8 +321,6 @@ The following optimizers are supported:
 - `sgd`: Stochastic Gradient Descent
 - `adagrad`: Adagrad optimizer
 
-
-
 ## Notes
 
 - Set `load_in_8bit: true` or `load_in_4bit: true` for memory-efficient training
@@ -347,10 +330,6 @@ The following optimizers are supported:
 
 For more detailed information, please refer to the [documentation](https://axolotl-ai-cloud.github.io/axolotl/docs/config.html).
 
-
 ### Errors:
+
 - if you face any issues with the Flash Attention-2, Delete yoor worker and Re-start.
-
-
-
-