use fastchat conversations template (#578)

* use fastchat conversations template

* require fastchat (fschat) pip install

* handle roles dynamically from conversation

* tweak fastchat conversation with a monkeypatch to get individual turns

* fix up so it works with multiple conversation styles, and don't strip the turns

* fix sharegpt fixture now that we're using a more correct tokenization

* use a new prompter and support fastchat conversation type

* use sharegpt from prompt strategies now

* update docs, add chatml template

* add a newline after im_end token

* ensure we correctly set system message

* update per PR feedback to handle deprecated sharegpt types

* don't add duplicate wandb req

* make sharegpt fields configurable from yml

* llama2 fixes

* don't fail fatally when turns are improper

tests/test_prompt_tokenizers.py

@@ -21,7 +21,7 @@ from axolotl.prompt_tokenizers import (
     AlpacaPromptTokenizingStrategy,
     ShareGPTPromptTokenizingStrategy,
 )
-from axolotl.prompters import AlpacaPrompter, PromptStyle, ShareGPTPrompter
+from axolotl.prompters import AlpacaPrompter, PromptStyle, ShareGPTPrompterV2
 
 LOG = logging.getLogger("axolotl")
 
@@ -60,7 +60,7 @@ class TestPromptTokenizationStrategies(unittest.TestCase):
         ) as fin:
             data = fin.read()
             tokenized_conversation = json.loads(data)
-        prompter = ShareGPTPrompter("chat")
+        prompter = ShareGPTPrompterV2()
         strat = ShareGPTPromptTokenizingStrategy(
             prompter,
             self.tokenizer,
@@ -79,7 +79,7 @@ class TestPromptTokenizationStrategies(unittest.TestCase):
         ) as fin:
             data = fin.read()
             conversation = json.loads(data)
-        prompter = ShareGPTPrompter("chat")
+        prompter = ShareGPTPrompterV2()
         strat = ShareGPTPromptTokenizingStrategy(
             prompter,
             self.tokenizer,