commit files to HF hub

README.md

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+---
+language:
+- en
+tags:
+- openvino
+---
+
+# declare-lab/flan-alpaca-xl
+
+This is the [declare-lab/flan-alpaca-xl](https://huggingface.co/declare-lab/flan-alpaca-xl) model converted to [OpenVINO](https://openvino.ai), for accellerated inference.
+
+An example of how to do inference on this model:
+```python
+from optimum.intel.openvino import OVModelForSeq2SeqLM
+from transformers import AutoTokenizer, pipeline
+
+# model_id should be set to either a local directory or a model available on the HuggingFace hub.
+model_id = "helenai/declare-lab-flan-alpaca-xl-ov"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = OVModelForSeq2SeqLM.from_pretrained(model_id)
+pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+result = pipe("hello world")
+print(result)
+```
+

config.json

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+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
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+  "d_kv": 64,
+  "d_model": 2048,
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+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
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+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 512,
+  "num_decoder_layers": 24,
+  "num_heads": 32,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
+    "summarization": {
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+      "length_penalty": 2.0,
+      "max_length": 200,
+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
+      "num_beams": 4,
+      "prefix": "summarize: "
+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.28.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32128
+}

inference.py

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+from optimum.intel.openvino import OVModelForSeq2SeqLM
+from transformers import AutoTokenizer, pipeline
+
+# model_id should be set to either a local directory or a model available on the HuggingFace hub.
+model_id = "helenai/declare-lab-flan-alpaca-xl-ov"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = OVModelForSeq2SeqLM.from_pretrained(model_id)
+pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+result = pipe("hello world")
+print(result)

openvino_decoder_model.bin

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openvino_decoder_with_past_model.bin

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openvino_encoder_model.bin

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