Mert commited on
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1 Parent(s): 86cafbf

Push model using huggingface_hub.

Browse files
README.md CHANGED
@@ -1,43 +1,43 @@
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- ---
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- license: apache-2.0
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- tags:
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- - trl
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- - ppo
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- - transformers
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- - reinforcement-learning
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- ---
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-
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- # TRL Model
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-
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- This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
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- guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
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-
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- ## Usage
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-
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- To use this model for inference, first install the TRL library:
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-
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- ```bash
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- python -m pip install trl
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- ```
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-
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- You can then generate text as follows:
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-
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- ```python
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- from transformers import pipeline
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-
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- generator = pipeline("text-generation", model="gulmert89/C:\Users\Mert\AppData\Local\Temp\tmpkiciuyxj\gulmert89\mistral-ppo")
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- outputs = generator("Hello, my llama is cute")
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- ```
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-
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- If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
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-
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- ```python
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- from transformers import AutoTokenizer
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- from trl import AutoModelForCausalLMWithValueHead
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-
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- tokenizer = AutoTokenizer.from_pretrained("gulmert89/C:\Users\Mert\AppData\Local\Temp\tmpkiciuyxj\gulmert89\mistral-ppo")
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- model = AutoModelForCausalLMWithValueHead.from_pretrained("gulmert89/C:\Users\Mert\AppData\Local\Temp\tmpkiciuyxj\gulmert89\mistral-ppo")
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-
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- inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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- outputs = model(**inputs, labels=inputs["input_ids"])
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- ```
 
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - trl
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+ - ppo
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+ - transformers
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+ - reinforcement-learning
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+ ---
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+
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+ # TRL Model
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+
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+ This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
13
+ guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
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+
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+ ## Usage
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+
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+ To use this model for inference, first install the TRL library:
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+
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+ ```bash
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+ python -m pip install trl
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+ ```
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+
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+ You can then generate text as follows:
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ generator = pipeline("text-generation", model="gulmert89//tmp/tmphxi1_39z/gulmert89/mistral-ppo")
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+ outputs = generator("Hello, my llama is cute")
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+ ```
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+
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+ If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
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+
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+ ```python
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+ from transformers import AutoTokenizer
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+ from trl import AutoModelForCausalLMWithValueHead
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+
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+ tokenizer = AutoTokenizer.from_pretrained("gulmert89//tmp/tmphxi1_39z/gulmert89/mistral-ppo")
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+ model = AutoModelForCausalLMWithValueHead.from_pretrained("gulmert89//tmp/tmphxi1_39z/gulmert89/mistral-ppo")
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+
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+ inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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+ outputs = model(**inputs, labels=inputs["input_ids"])
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+ ```
config.json CHANGED
@@ -1,27 +1,28 @@
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- }
 
 
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+ }
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