Update README.md

README.md

@@ -12,101 +12,11 @@ model-index:
 
 [<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)
 
+### Model Description
 
-# Axolotl Config 
+A model that can generate [Honeycomb Queries](https://www.honeycomb.io/blog/introducing-query-assistant).  
 
-axolotl version: `0.3.0`
-```yaml
-base_model: mistralai/Mistral-7B-v0.1
-model_type: MistralForCausalLM
-tokenizer_type: LlamaTokenizer
-is_mistral_derived_model: true
-
-load_in_8bit: false
-load_in_4bit: true
-strict: false
-
-lora_fan_in_fan_out: false
-data_seed: 49
-seed: 49
-
-datasets:
-  - path: _synth_data/alpaca_synth_queries_healed.jsonl
-    type: sharegpt
-    conversation: alpaca
-dataset_prepared_path: last_run_prepared
-val_set_size: 0.1
-output_dir: ./qlora-alpaca-out
-hub_model_id: hamel/hc-mistral-alpaca
-
-adapter: qlora
-lora_model_dir:
-
-sequence_len: 896
-sample_packing: false
-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
-  - down_proj
-  - up_proj
-  - q_proj
-  - v_proj
-  - k_proj
-  - o_proj
-
-wandb_project: hc-axolotl-mistral
-wandb_entity: hamelsmu
-
-gradient_accumulation_steps: 4
-micro_batch_size: 16
-eval_batch_size: 16
-num_epochs: 3
-optimizer: adamw_bnb_8bit
-lr_scheduler: cosine
-learning_rate: 0.0002
-max_grad_norm: 1.0
-adam_beta2: 0.95
-adam_epsilon: 0.00001
-save_total_limit: 12
-
-train_on_inputs: false
-group_by_length: false
-bf16: true
-fp16: false
-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: 20
-evals_per_epoch: 4
-eval_table_size:
-eval_table_max_new_tokens: 128
-saves_per_epoch: 6
-debug:
-weight_decay: 0.0
-fsdp:
-fsdp_config:
-special_tokens:
-  bos_token: "<s>"
-  eos_token: "</s>"
-  unk_token: "<unk>"
-save_safetensors: true
-```
+_fine-tuned by [Hamel Husain](https://hamel.dev)_ 
 
 # hc-mistral-alpaca
 
@@ -156,16 +66,30 @@ def prompt_tok(nlq, cols):
 Finally, you can get predictions like this:
 
 ```python
+# model inputs
 nlq = "Exception count by exception and caller"
 cols = ['error', 'exception.message', 'exception.type', 'exception.stacktrace', 'SampleRate', 'name', 'db.user', 'type', 'duration_ms', 'db.name', 'service.name', 'http.method', 'db.system', 'status_code', 'db.operation', 'library.name', 'process.pid', 'net.transport', 'messaging.system', 'rpc.system', 'http.target', 'db.statement', 'library.version', 'status_message', 'parent_name', 'aws.region', 'process.command', 'rpc.method', 'span.kind', 'serializer.name', 'net.peer.name', 'rpc.service', 'http.scheme', 'process.runtime.name', 'serializer.format', 'serializer.renderer', 'net.peer.port', 'process.runtime.version', 'http.status_code', 'telemetry.sdk.language', 'trace.parent_id', 'process.runtime.description', 'span.num_events', 'messaging.destination', 'net.peer.ip', 'trace.trace_id', 'telemetry.instrumentation_library', 'trace.span_id', 'span.num_links', 'meta.signal_type', 'http.route']
+
+# print prediction
+out = prompt_tok(nlq, cols)
+print(nlq, '\n', out)
 ```
 
+This will give you a prediction that looks like this:
+
+  ```md
+  "{'breakdowns': ['exception.message', 'exception.type'], 'calculations': [{'op': 'COUNT'}], 'filters': [{'column': 'exception.message', 'op': 'exists'}, {'column': 'exception.type', 'op': 'exists'}], 'orders': [{'op': 'COUNT', 'order': 'descending'}], 'time_range': 7200}"
+  ```
+
 Alternatively, you can play with this model on Replicate: [hamelsmu/honeycomb-2](https://replicate.com/hamelsmu/honeycomb-2)
 
 # Hosted Inference
 
 This model is hosted on Replicate: (hamelsmu/honeycomb-2)[https://replicate.com/hamelsmu/honeycomb-2], using [this config](https://github.com/hamelsmu/replicate-examples/tree/master/mistral-transformers-2).
 
+# Training Procedure 
+
+Used [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl/tree/main), see [this config](config/axolotl_config.yml).
 
 ### Framework versions