Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Run this model inference with full control and performance in your environment.
Get help setting up a custom Dedicated Endpoints.
Talk with our engineer to get a quote for reserved GPU instances with discounts.
README
Training Configuration
| Parameter | Value |
|---|---|
| Training Mode | SFT |
| Base Model | nbeerbower/A2-Hemlock-Coder |
| Learning Rate | 0.0001 |
| Epochs | 1 |
| Batch Size | 1 |
| Gradient Accumulation | 32 |
| Effective Batch Size | 32 |
| Max Sequence Length | 2048 |
| Optimizer | paged_adamw_8bit |
| LR Scheduler | cosine |
| Warmup Ratio | 0.05 |
| Weight Decay | 0.01 |
| Max Grad Norm | 0.5 |
| Seed | 42 |
| LoRA Rank (r) | 64 |
| LoRA Alpha | 128 |
| LoRA Dropout | 0.05 |
| Target Modules | up_proj, down_proj, gate_proj, k_proj, q_proj, v_proj, o_proj |
| Quantization | 4-bit (NF4) |
| GPU | NVIDIA RTX A6000 |
Reproduce this training run
This model was trained with Merlina. Save the JSON below to data/configs/<name>.json (or import it via the Load Configuration dialog) to reproduce the exact training setup. Credentials are not included — Merlina will use your own HF_TOKEN and WANDB_API_KEY from .env or the form.
json
{"_metadata": {"name": "A2-Hemlock-Coder-Claude-opus-4.6-TraceInversion-9000x-SFT","description": "Training configuration shared from a Merlina-trained model.","tags": [],"schema": "merlina/training-config","schema_version": 1,"merlina_version": "2.0.1"},"base_model": "nbeerbower/A2-Hemlock-Coder","output_name": "A2-Hemlock-Coder-Claude-opus-4.6-TraceInversion-9000x-SFT","use_lora": true,"lora_r": 64,"lora_alpha": 128,"lora_dropout": 0.05,"target_modules": ["up_proj","down_proj","gate_proj","k_proj","q_proj","v_proj","o_proj"],"modules_to_save": [],"lora_task_type": "CAUSAL_LM","learning_rate": 0.0001,"num_epochs": 1,"batch_size": 1,"gradient_accumulation_steps": 32,"max_length": 2048,"max_prompt_length": 1024,"model_type": "auto","training_mode": "sft","beta": 0.1,"label_smoothing": 0.0,"gamma": 0.5,"vision_model_id": null,"stage": null,"unfreeze_vision_top_n": null,"image_token_id": null,"min_pixels": null,"max_pixels": null,"image_column": null,"caption_column": null,"instruction": null,"streaming": null,"model_name": null,"image_resolution": 1024,"lora_rank": 32,"lora_target_modules": null,"dataset_jsonl_path": null,"dataset_name": null,"dataset_split": null,"sample_prompts": null,"sample_num_steps": null,"dataset": {"source": {"source_type": "huggingface","repo_id": "Jackrong/Claude-opus-4.6-TraceInversion-9000x","split": "train","file_path": null,"file_format": null,"dataset_id": null,"streaming": false,"streaming_batch_size": 10000,"column_mapping": null},"additional_sources": [],"format": {"format_type": "tokenizer","custom_templates": null,"enable_thinking": true},"model_name": "nbeerbower/A2-Hemlock-Coder","column_mapping": {"input": "prompt","output": "chosen","reasoning_bubble": "reasoning"},"convert_messages_format": false,"deduplicate": false,"dedupe_strategy": "prompt_chosen","test_size": 0.01,"max_samples": null,"system_prompt": null,"system_prompt_mode": "fill_empty","training_mode": "sft"},"seed": 42,"max_grad_norm": 0.5,"warmup_ratio": 0.05,"eval_steps": 0.2,"use_4bit": true,"use_wandb": true,"push_to_hub": true,"merge_lora_before_upload": true,"hf_hub_private": true,"export_gguf": false,"gguf_quant_types": ["Q4_K_M"],"keep_gguf_fp16": false,"shuffle_dataset": true,"weight_decay": 0.01,"lr_scheduler_type": "cosine","gradient_checkpointing": true,"logging_steps": 1,"optimizer_type": "paged_adamw_8bit","adam_beta1": 0.9,"adam_beta2": 0.999,"adam_epsilon": 1e-08,"adafactor_relative_step": false,"adafactor_scale_parameter": false,"adafactor_warmup_init": false,"adafactor_decay_rate": -0.8,"adafactor_beta1": null,"adafactor_clip_threshold": 1.0,"attn_implementation": "auto","use_liger": true,"torch_compile": false,"neftune_alpha": null,"eval_on_start": true,"gpu_ids": null,"multi_gpu_strategy": "auto","wandb_project": null,"wandb_run_name": null,"wandb_tags": null,"wandb_notes": null}

Model provider
nbeerbower
Model tree
Base
nbeerbower/A2-Hemlock-Coder
Fine-tuned
this model
Modalities
Input
Text
Output
Text
Pricing
Dedicated Endpoints
View detailsSupported Functionality
Model APIs
Dedicated Endpoints
Container
More information