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text generation inference infos

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  1. README.md +34 -0
README.md CHANGED
@@ -151,6 +151,40 @@ for i, t in enumerate(generated_text):
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  print(f"{i}:\n{t}\n")
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  ```
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  # Training Details
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  ## IDEFICS
 
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  print(f"{i}:\n{t}\n")
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  ```
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+ ## Text generation inference
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+
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+ The hosted inference API is powered by [Text Generation Inference](https://github.com/huggingface/text-generation-inference). To query the model, you can use the following code snippet. The key is to pass images as fetchable URLs with the markdown syntax:
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+ ```
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+ from text_generation import Client
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+
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+ API_TOKEN = "<YOUR_API_TOKEN>"
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+ API_URL = "https://api-inference.huggingface.co/models/HuggingFaceM4/idefics-80b-instruct"
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+ DECODING_STRATEGY = "Greedy"
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+ QUERY = "User: What is in this image?![](https://upload.wikimedia.org/wikipedia/commons/8/86/Id%C3%A9fix.JPG)<end_of_utterance>\nAssistant:"
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+
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+ client = Client(
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+ base_url=API_URL,
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+ headers={"x-use-cache": "0", "Authorization": f"Bearer {API_TOKEN}"},
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+ )
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+ generation_args = {
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+ "max_new_tokens": 256,
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+ "repetition_penalty": 1.0,
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+ "stop_sequences": ["<end_of_utterance>", "\nUser:"],
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+ }
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+
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+ if DECODING_STRATEGY == "Greedy":
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+ generation_args["do_sample"] = False
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+ elif DECODING_STRATEGY == "Top P Sampling":
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+ generation_args["temperature"] = 1.
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+ generation_args["do_sample"] = True
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+ generation_args["top_p"] = 0.95
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+
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+ generated_text = client.generate(prompt=QUERY, **generation_args)
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+ print(generated_text)
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+ ```
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+
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+ Note that we currently only host the inference for the instructed models.
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+
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  # Training Details
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  ## IDEFICS