Add PyTorch model files

README.md

@@ -1,100 +1,58 @@
 ---
-tags:
-- pytorch
-- safetensors
-- transformers
-- gpt-oss
-- multilingual
-- text-generation
-language:
-- en
-- es
-- fr
-- de
-- it
-- pt
-license: apache-2.0
-model_type: gpt-oss
-pipeline_tag: text-generation
 base_model: openai/gpt-oss-20b
+library_name: transformers
+model_name: fine_tuned
+tags:
+- generated_from_trainer
+- trl
+- sft
+licence: license
 ---
 
-# GPT-OSS-20B Function Calling Model
-
-This repository contains the GPT-OSS-20B model fine-tuned on function calling data in PyTorch/Safetensors format, ready for use with the Transformers library.
-
-## Model Details
-
-- **Base Model:** openai/gpt-oss-20b
-- **Fine-tuning Dataset:** Salesforce/xlam-function-calling-60k (2000 samples)
-- **Fine-tuning Method:** LoRA (r=8, alpha=16)
-- **Context Length:** 131,072 tokens
-- **Model Size:** 20B parameters
-
-## Files
-
-- `model.safetensors`: Model weights in Safetensors format
-- `config.json`: Model configuration
-- `tokenizer.json`, `tokenizer_config.json`: Tokenizer files
-- `generation_config.json`: Generation configuration
+# Model Card for fine_tuned
 
-## Usage
+This model is a fine-tuned version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b).
+It has been trained using [TRL](https://github.com/huggingface/trl).
 
-### With Transformers Library
+## Quick start
 
 ```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import pipeline
 
-# Load model and tokenizer
-model = AutoModelForCausalLM.from_pretrained(
-    "cuijian0819/gpt-oss-20b-function-calling",
-    torch_dtype="auto",
-    device_map="auto"
-)
-tokenizer = AutoTokenizer.from_pretrained("cuijian0819/gpt-oss-20b-function-calling")
-
-# Generate text
-inputs = tokenizer("Your prompt here", return_tensors="pt")
-outputs = model.generate(**inputs, max_length=100, temperature=0.7)
-response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+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="cuijian0819/fine_tuned", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
 ```
 
-### Fine-tuning
-
-This model can be further fine-tuned using standard PyTorch/Transformers workflows:
+## Training procedure
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer, Trainer, TrainingArguments
+ 
 
-model = AutoModelForCausalLM.from_pretrained("cuijian0819/gpt-oss-20b-function-calling")
-tokenizer = AutoTokenizer.from_pretrained("cuijian0819/gpt-oss-20b-function-calling")
 
-# Your fine-tuning code here
-```
+This model was trained with SFT.
 
-## GGUF Version
+### Framework versions
 
-For efficient inference with llama.cpp or Ollama, check out the GGUF version: [cuijian0819/gpt-oss-20b-function-calling-gguf](https://huggingface.co/cuijian0819/gpt-oss-20b-function-calling-gguf)
+- TRL: 0.21.0
+- Transformers: 4.55.0
+- Pytorch: 2.7.1+cu118
+- Datasets: 4.0.0
+- Tokenizers: 0.21.4
 
-## Training Details
+## Citations
 
-- **Training Epochs:** 2
-- **Learning Rate:** 0.0002
-- **Batch Size:** 4
-- **Gradient Accumulation:** 4
-- **Max Length:** 1024
 
-## License
-
-This model inherits the license from the base openai/gpt-oss-20b model.
-
-## Citation
 
+Cite TRL as:
+    
 ```bibtex
-@misc{gpt-oss-20b-function-calling,
-  title={GPT-OSS-20B Function Calling Model},
-  author={cuijian0819},
-  year={2025},
-  url={https://huggingface.co/cuijian0819/gpt-oss-20b-function-calling}
+@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 Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
 }
-```
+```