Create README.md

README.md

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+---
+base_model: Qwen/Qwen2-1.5B
+datasets: 
+- macadeliccc/opus_samantha
+- teknium/OpenHermes-2.5
+- cognitivecomputations/samantha-data
+- cognitivecomputations/samantha-1.5
+- jondurbin/airoboros-3.2
+- microsoft/orca-math-word-problems-200k
+- Sao10K/Claude-3-Opus-Instruct-15K
+- Locutusque/function-calling-chatml
+- Migtissera/Hitchhikers
+---
+# Samantha Qwen2 1.5B
+
+This model was trained on 2xL40S using FSDP and QLoRa. Adapter is available [here](https://huggingface.co/macadeliccc/Samantha-Qwen2-1.5B-QLoRa).
+
+## Prompt Template
+
+```
+<|im_start|>system
+You are a helpful AI assistant<|im_end|>
+<|im_start|>user
+What is the capital of France?<|im_end|>
+<|im_start|>assistant
+```
+
+## Launch Using VLLM
+
+```bash
+python -m vllm.entrypoints.openai.api_server \
+    --model macadeliccc/Samantha-Qwen2-1.5B \
+    --chat-template ./examples/template_chatml.jinja \
+```
+
+```python
+from openai import OpenAI
+# Set OpenAI's API key and API base to use vLLM's API server.
+openai_api_key = "EMPTY"
+openai_api_base = "http://localhost:8000/v1"
+
+client = OpenAI(
+    api_key=openai_api_key,
+    base_url=openai_api_base,
+)
+
+chat_response = client.chat.completions.create(
+    model="macadeliccc/Samantha-Qwen-2-7B",
+    messages=[
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Tell me a joke."},
+    ]
+)
+print("Chat response:", chat_response)
+```
+
+## Quants
+
+TODO
+
+## Config
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.0`
+```yaml
+base_model: Qwen/Qwen2-1.5B
+trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+datasets:
+  - path: macadeliccc/opus_samantha
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: uncensored_ultrachat_20k_sharegpt.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: flattened_openhermes_200k.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: opus_instruct.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: airoboros_uncensored.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: orca_math_word_problems_sharegpt.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: sharegpt_starcoder.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: samantha_1.1_uncensored.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: samantha_1.5.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+  - path: json
+    data_files: sharegpt_hitchhikers_v1.json
+    type: sharegpt
+    field: conversations
+    conversation: chatml
+
+
+chat_template: chatml
+
+
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./outputs/out
+
+sequence_len: 4096
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+adapter: qlora
+lora_model_dir:
+lora_r: 32
+lora_alpha: 64
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 1
+num_epochs: 3
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 0.0002
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: true
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10
+evals_per_epoch: 4
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+  - full_shard
+  - auto_wrap
+fsdp_config:
+  fsdp_limit_all_gathers: true
+  fsdp_sync_module_states: true
+  fsdp_offload_params: true
+  fsdp_use_orig_params: false
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
+  fsdp_state_dict_type: FULL_STATE_DICT
+special_tokens:
+```
+
+</details><br>
+
+