commit files to HF hub

README.md

@@ -7,9 +7,11 @@ tags:
 
 # mistralai/Mistral-7B-Instruct-v0.2
 
-This is the [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) model, quantized with An example of how to do inference on this model:
+This is the [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) model converted to [OpenVINO](https://openvino.ai), for accelerated inference.
+
+An example of how to do inference on this model:
 ```python
-from optimum.intel.openvino import OVModelForCausalLM
+from optimum.intel import OVModelForCausalLM
 from transformers import AutoTokenizer, pipeline
 
 # model_id should be set to either a local directory or a model available on the HuggingFace hub.

config.json

@@ -21,7 +21,7 @@
   "sliding_window": null,
   "tie_word_embeddings": false,
   "torch_dtype": "bfloat16",
-  "transformers_version": "4.37.2",
+  "transformers_version": "4.40.2",
   "use_cache": true,
   "vocab_size": 32000
 }

inference.py

@@ -1,10 +1,10 @@
-from optimum.intel.openvino import OVModelForCausalLM
+from optimum.intel import OVModelForCausalLM
 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/mistralai-Mistral-7B-Instruct-v0.2-ov"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = OVModelForCausalLM.from_pretrained(model_id, revision='int8-ptq')
+model = OVModelForCausalLM.from_pretrained(model_id)
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 result = pipe("hello world")
 print(result)

openvino_model.bin

@@ -1,3 +1,3 @@
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+size 14500241654

tokenizer.json

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