[docs] Update README Quickstart to use CLI (#2137)

* update quickstart for new CLI

* add blurb about bleeding edge builds

* missed a yaml reference

* prefer lora over qlora for examples

* fix commands for parity with previous instructions

* consistency on pip/pip3 install

* one more parity pip=>pip3

* remove extraneous options in example yaml

Co-authored-by: NanoCode012 <nano@axolotl.ai>

* update copy

* update badges and for discord and socials in readme

* Fix a few broken links

* bump version to 0.6.0 for release

---------

Co-authored-by: NanoCode012 <nano@axolotl.ai>

README.md

@@ -10,9 +10,13 @@
     <img src="https://img.shields.io/github/license/axolotl-ai-cloud/axolotl.svg?color=blue" alt="GitHub License">
     <img src="https://github.com/axolotl-ai-cloud/axolotl/actions/workflows/tests.yml/badge.svg" alt="tests">
     <a href="https://github.com/axolotl-ai-cloud/axolotl/releases"><img src="https://img.shields.io/github/release/axolotl-ai-cloud/axolotl.svg" alt="Releases"></a>
+    <br/>
+    <a href="https://github.com/axolotl-ai-cloud/axolotl/graphs/contributors"><img src="https://img.shields.io/github/contributors-anon/axolotl-ai-cloud/axolotl?color=yellow&style=flat-square" alt="contributors" style="height: 20px;"></a>
     <img src="https://img.shields.io/github/stars/axolotl-ai-cloud/axolotl" alt="GitHub Repo stars">
-</p>
+    <br/>
-<p align="center">
+    <a href="https://discord.com/invite/HhrNrHJPRb"><img src="https://img.shields.io/badge/discord-7289da.svg?style=flat-square&logo=discord" alt="discord" style="height: 20px;"></a>
+    <a href="https://twitter.com/axolotl_ai"><img src="https://img.shields.io/twitter/follow/axolotl_ai?style=social" alt="twitter" style="height: 20px;"></a>
+    <br/>
     <img src="https://github.com/axolotl-ai-cloud/axolotl/actions/workflows/tests-nightly.yml/badge.svg" alt="tests-nightly">
     <img src="https://github.com/axolotl-ai-cloud/axolotl/actions/workflows/multi-gpu-e2e.yml/badge.svg" alt="multigpu-semi-weekly tests">
 </p>
@@ -42,7 +46,8 @@ Features:
 - [Axolotl](#axolotl)
   - [Table of Contents](#table-of-contents)
   - [Quickstart ⚡](#quickstart-)
-    - [Usage](#usage)
+    - [Edge Builds](#edge-builds-)
+    - [Axolotl CLI Usage](#axolotl-cli-usage)
   - [Badge ❤🏷️](#badge-️)
   - [Contributing 🤝](#contributing-)
   - [Sponsors 🤝❤](#sponsors-)
@@ -107,58 +112,49 @@ Get started with Axolotl in just a few steps! This quickstart guide will walk yo
 **Requirements**: *Nvidia* GPU (Ampere architecture or newer for `bf16` and Flash Attention) or *AMD* GPU, Python >=3.10 and PyTorch >=2.3.1.
 
 ```bash
-git clone https://github.com/axolotl-ai-cloud/axolotl
+pip3 install axolotl[flash-attn,deepspeed]
-cd axolotl
 
+# download examples and optionally deepspeed configs to the local path
+axolotl fetch examples
+axolotl fetch deepspeed_configs  # OPTIONAL
+
+# finetune using lora
+axolotl train examples/llama-3/lora-1b.yml
+```
+
+### Edge Builds 🏎️
+
+If you're looking for the latest features and updates between releases, you'll need to install
+from source.
+
+```bash
+git clone https://github.com/axolotl-ai-cloud/axolotl.git
+cd axolotl
 pip3 install packaging ninja
 pip3 install -e '.[flash-attn,deepspeed]'
 ```
 
-### Usage
+### Axolotl CLI Usage
-```bash
+We now support a new, more streamlined CLI using [click](https://click.palletsprojects.com/en/stable/).
-# preprocess datasets - optional but recommended
-CUDA_VISIBLE_DEVICES="0" python -m axolotl.cli.preprocess examples/openllama-3b/lora.yml
-
-# finetune lora
-accelerate launch -m axolotl.cli.train examples/openllama-3b/lora.yml
-
-# inference
-accelerate launch -m axolotl.cli.inference examples/openllama-3b/lora.yml \
-    --lora_model_dir="./outputs/lora-out"
-
-# gradio
-accelerate launch -m axolotl.cli.inference examples/openllama-3b/lora.yml \
-    --lora_model_dir="./outputs/lora-out" --gradio
-
-# remote yaml files - the yaml config can be hosted on a public URL
-# Note: the yaml config must directly link to the **raw** yaml
-accelerate launch -m axolotl.cli.train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/openllama-3b/lora.yml
-```
-
-### Axolotl CLI
-
-If you've installed this package using `pip` from source, we now support a new, more
-streamlined CLI using [click](https://click.palletsprojects.com/en/stable/). Rewriting
-the above commands:
 
 ```bash
 # preprocess datasets - optional but recommended
-CUDA_VISIBLE_DEVICES="0" axolotl preprocess examples/openllama-3b/lora.yml
+CUDA_VISIBLE_DEVICES="0" axolotl preprocess examples/llama-3/lora-1b.yml
 
 # finetune lora
-axolotl train examples/openllama-3b/lora.yml
+axolotl train examples/llama-3/lora-1b.yml
 
 # inference
-axolotl inference examples/openllama-3b/lora.yml \
+axolotl inference examples/llama-3/lora-1b.yml \
     --lora-model-dir="./outputs/lora-out"
 
 # gradio
-axolotl inference examples/openllama-3b/lora.yml \
+axolotl inference examples/llama-3/lora-1b.yml \
     --lora-model-dir="./outputs/lora-out" --gradio
 
 # remote yaml files - the yaml config can be hosted on a public URL
 # Note: the yaml config must directly link to the **raw** yaml
-axolotl train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/openllama-3b/lora.yml
+axolotl train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/llama-3/lora-1b.yml
 ```
 
 We've also added a new command for fetching `examples` and `deepspeed_configs` to your
@@ -175,6 +171,36 @@ axolotl fetch deepspeed_configs
 axolotl fetch examples --dest path/to/folder
 ```
 
+### Legacy Usage
+<details>
+
+<summary>Click to Expand</summary>
+
+While the Axolotl CLI is the preferred method for interacting with axolotl, we
+still support the legacy `-m axolotl.cli.*` usage.
+
+```bash
+# preprocess datasets - optional but recommended
+CUDA_VISIBLE_DEVICES="0" python -m axolotl.cli.preprocess examples/llama-3/lora-1b.yml
+
+# finetune lora
+accelerate launch -m axolotl.cli.train examples/llama-3/lora-1b.yml
+
+# inference
+accelerate launch -m axolotl.cli.inference examples/llama-3/lora-1b.yml \
+    --lora_model_dir="./outputs/lora-out"
+
+# gradio
+accelerate launch -m axolotl.cli.inference examples/llama-3/lora-1b.yml \
+    --lora_model_dir="./outputs/lora-out" --gradio
+
+# remote yaml files - the yaml config can be hosted on a public URL
+# Note: the yaml config must directly link to the **raw** yaml
+accelerate launch -m axolotl.cli.train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/llama-3/lora-1b.yml
+```
+
+</details>
+
 ## Badge ❤🏷️
 
 Building something cool with Axolotl? Consider adding a badge to your model card.

examples/llama-3/lora-1b.yml

@@ -0,0 +1,74 @@
+base_model: NousResearch/Llama-3.2-1B
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: teknium/GPT4-LLM-Cleaned
+    type: alpaca
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.1
+output_dir: ./outputs/lora-out
+
+adapter: lora
+lora_model_dir:
+
+sequence_len: 2048
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+lora_r: 16
+lora_alpha: 32
+lora_dropout: 0.05
+lora_fan_in_fan_out:
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 2
+micro_batch_size: 2
+num_epochs: 1
+optimizer: adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+loss_watchdog_threshold: 5.0
+loss_watchdog_patience: 3
+
+warmup_steps: 10
+evals_per_epoch: 4
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  pad_token: "<|end_of_text|>"

examples/llama-3/qlora-1b.yml

@@ -1,4 +1,4 @@
-base_model: meta-llama/Llama-3.2-1B
+base_model: NousResearch/Llama-3.2-1B
 
 load_in_8bit: false
 load_in_4bit: true
@@ -22,7 +22,6 @@ pad_to_sequence_len: true
 lora_r: 32
 lora_alpha: 16
 lora_dropout: 0.05
-lora_target_linear: true
 lora_fan_in_fan_out:
 lora_target_modules:
   - gate_proj

src/axolotl/__init__.py

@@ -1,3 +1,3 @@
 """Axolotl - Train and fine-tune large language models"""
 
-__version__ = "0.5.3.dev0"
+__version__ = "0.6.0"