Upload LoRA adapter trained with Tinker

Base model: meta-llama/Llama-3.1-8B
Tinker checkpoint: tinker://7f4705e7-551f-5133-b4bb-33444c0c405b:train:0/sampler_weights/test-push-to-hub
Uploaded: 2025-12-28T22:17:23.954862

README.md

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+---
+library_name: peft
+base_model: meta-llama/Llama-3.1-8B
+tags:
+- tinker
+- lora
+- sl
+license: llama3.1
+---
+
+# joschu0/tinker-llama-lora-test
+
+This model is a [LoRA adapter](https://huggingface.co/docs/peft/main/en/conceptual_guides/lora) fine-tuned with **[Tinker](https://thinkingmachines.ai/tinker)** from [Thinking Machines Lab](https://thinkingmachines.ai).
+
+## Model Details
+
+| Attribute | Value |
+|-----------|-------|
+| **Base Model** | [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) |
+| **Training Type** | Supervised Learning (SFT) |
+| **LoRA Rank** | 8 |
+| **LoRA Alpha** | 32 |
+| **Target Modules** | all-linear |
+
+
+## Usage
+
+### With PEFT
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load base model
+base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B")
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B")
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(base_model, "joschu0/tinker-llama-lora-test")
+```
+
+### With Tinker (for continued training)
+
+```python
+import tinker
+
+sc = tinker.ServiceClient()
+# Note: The checkpoint must be published on Tinker for this to work
+training_client = sc.create_training_client_from_state("tinker://7f4705e7-551f-5133-b4bb-33444c0c405b:train:0/sampler_weights/test-push-to-hub")
+```
+
+## Training
+
+This model was trained using the Tinker API. For more information about training
+with Tinker, see the [Tinker documentation](https://tinker-docs.thinkingmachines.ai/).
+
+
+
+---
+
+<p align="center">
+  <em>Trained with <a href="https://thinkingmachines.ai/tinker">Tinker</a> by Thinking Machines Lab</em>
+</p>

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Llama-3.1-8B",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": false,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": "all-linear",
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 88180792