Duplicate from DrNicefellow/Mistral-7-from-Mixtral-8x7B-v0.1

Co-authored-by: Dr. Nicefellow <[email protected]>

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NOTICE

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+This product includes the Mixtral-8x7B-v0.1 Extracted Model 7, which was derived from the `mistralai/Mixtral-8x7B-v0.1` model available on Hugging Face under the Apache 2.0 License.
+
+=========================================================================
+
+This model is the 7th extracted standalone model from mistralai/Mixtral-8x7B--v0.1, which is provided by mistralai and its contributors. The original model is available under the Apache 2.0 License, and this extracted model inherits that license.
+
+For the original model and contributions, please see the model page on Hugging Face or contact the developers directly.
+
+The Apache 2.0 License details for the `mistralai/Mixtral-8x7B-v0.1` model apply to this extracted model. For the full Apache 2.0 License, see the LICENSE file included with this distribution or visit http://www.apache.org/licenses/LICENSE-2.0.
+
+Acknowledgments:
+- The Apache Software Foundation (http://www.apache.org/)
+- mistralai and contributors for the development of the `mistralai/Mixtral-8x7B-v0.1` model.
+
+This NOTICE file is required by Apache 2.0 License and should not be altered. It must be included with any distribution of the model or derivatives thereof.

README.md

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+---
+license: apache-2.0
+---
+
+# Mixtral-8x7B--v0.1: Model 7
+
+## Model Description
+
+This model is the 7th extracted standalone model from the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1), using the [Mixtral Model Expert Extractor tool](https://github.com/MeNicefellow/Mixtral-Model-Expert-Extractor) I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is experimental. It is expected to be worse than Mistral-7B.
+
+## Model Architecture
+
+The architecture of this model includes:
+- Multi-head attention layers derived from the base Mixtral model.
+- The first expert from each MoE layer, intended to provide a balanced approach to language understanding and generation tasks.
+- Additional layers and components as required to ensure the model's functionality outside the MoE framework.
+
+
+### Example
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "DrNicefellow/Mistral-3-from-Mixtral-8x7B-v0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+text = "Today is a pleasant"
+input_ids = tokenizer.encode(text, return_tensors='pt')
+output = model.generate(input_ids)
+
+print(tokenizer.decode(output[0], skip_special_tokens=True))
+```
+
+## License
+
+This model is available under the Apache 2.0 License.
+
+
+## Discord Server
+
+Join our Discord server [here](https://discord.gg/xhcBDEM3).
+
+## License
+
+This model is open-sourced under the Apache 2.0 License. See the LICENSE file for more details.

config.json

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+{
+  "_name_or_path": "./mistralai_Mixtral-8x7B-v0.1/",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_experts_per_tok": 2,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "num_local_experts": 8,
+  "output_router_logits": false,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "router_aux_loss_coef": 0.02,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.38.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.38.0.dev0"
+}

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