Update README.md

README.md

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----
-license: apache-2.0
-tags:
-- trl
-- transformers
-- reinforcement-learning
----
-
-# TRL Model
-
-This is a [TRL language model](https://github.com/lvwerra/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="Evan-Lin//tmp/tmpuz01z58o/Evan-Lin/Bart-Yelp-rougelastbatch-attractive1-keywordmax1-encoderrep0.5-length0-rep0.5")
-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("Evan-Lin//tmp/tmpuz01z58o/Evan-Lin/Bart-Yelp-rougelastbatch-attractive1-keywordmax1-encoderrep0.5-length0-rep0.5")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmpuz01z58o/Evan-Lin/Bart-Yelp-rougelastbatch-attractive1-keywordmax1-encoderrep0.5-length0-rep0.5")
-
-inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
-outputs = model(**inputs, labels=inputs["input_ids"])
-```
+生很長的句子?