EdBerg/cohere_Baha_1A_cupper_in_gold

README.md

@@ -0,0 +1,57 @@
+---
+base_model: CohereForAI/c4ai-command-r7b-arabic-02-2025
+library_name: transformers
+model_name: cohere_Baha_1A_cupper_in_gold
+tags:
+- generated_from_trainer
+- trl
+- sft
+licence: license
+---
+
+# Model Card for cohere_Baha_1A_cupper_in_gold
+
+This model is a fine-tuned version of [CohereForAI/c4ai-command-r7b-arabic-02-2025](https://huggingface.co/CohereForAI/c4ai-command-r7b-arabic-02-2025).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="EdBerg/cohere_Baha_1A_cupper_in_gold", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/harpermia882/huggingface/runs/ha3bi4pf)
+
+This model was trained with SFT.
+
+### Framework versions
+
+- TRL: 0.12.0
+- Transformers: 4.48.3
+- Pytorch: 2.6.0+cu124
+- Datasets: 3.4.1
+- Tokenizers: 0.21.1
+
+## Citations
+
+
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

adapter_config.json

@@ -24,13 +24,13 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "down_proj",
+    "q_proj",
     "o_proj",
-    "gate_proj",
+    "k_proj",
     "v_proj",
     "up_proj",
-    "q_proj",
-    "k_proj"
+    "down_proj",
+    "gate_proj"
   ],
   "task_type": "CAUSAL_LM",
   "trainable_token_indices": null,

adapter_model.safetensors

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runs/Mar17_18-34-43_f2553125dbc1/events.out.tfevents.1742236485.f2553125dbc1.252.0

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special_tokens_map.json

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     "rstrip": false,
     "single_word": false
   },
-  "pad_token": "<|END_OF_TURN_TOKEN|>",
+  "pad_token": {
+    "content": "<PAD>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
   "unk_token": {
     "content": "<UNK>",
     "lstrip": false,

tokenizer.json

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tokenizer_config.json

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   "model_max_length": 1000000000000000019884624838656,
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+  "pad_token": "<PAD>",
   "sp_model_kwargs": {},
   "spaces_between_special_tokens": false,
   "tokenizer_class": "CohereTokenizer",

training_args.bin

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