Push model using huggingface_hub.

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,44 @@
+---
+license: apache-2.0
+library_name: transformers
+tags:
+- trl
+- ppo
+- transformers
+- reinforcement-learning
+---
+
+# TRL Model
+
+This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
+ guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
+
+## Usage
+
+To use this model for inference, first install the TRL library:
+
+```bash
+python -m pip install trl
+```
+
+You can then generate text as follows:
+
+```python
+from transformers import pipeline
+
+generator = pipeline("text-generation", model="arianaazarbal//tmp/tmpwsg6y4vk/arianaazarbal/hacking-it-thinking-model-focus-on-tests-20250624_025441")
+outputs = generator("Hello, my llama is cute")
+```
+
+If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
+
+```python
+from transformers import AutoTokenizer
+from trl import AutoModelForCausalLMWithValueHead
+
+tokenizer = AutoTokenizer.from_pretrained("arianaazarbal//tmp/tmpwsg6y4vk/arianaazarbal/hacking-it-thinking-model-focus-on-tests-20250624_025441")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("arianaazarbal//tmp/tmpwsg6y4vk/arianaazarbal/hacking-it-thinking-model-focus-on-tests-20250624_025441")
+
+inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
+outputs = model(**inputs, labels=inputs["input_ids"])
+```

adapter_config.json

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+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-3B-Instruct",
+  "bias": "none",
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+  "layer_replication": null,
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+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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added_tokens.json

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chat_template.jinja

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+{% for message in messages %}{% if message['role'] == 'user' %}{{ 'user\n' + message['content'] + '\n' }}{% elif message['role'] == 'assistant' %}{{ 'assistant\n' + message['content'] + '\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ 'assistant\n<thinking>\n' }}{% endif %}

config.json

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+  "project_kwargs": {},
+  "push_to_hub_if_best_kwargs": {},
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pytorch_model.bin

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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