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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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- orpo
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- generated_from_trainer
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- mlx
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base_model: mistral-community/Mixtral-8x22B-v0.1
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datasets:
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- argilla/distilabel-capybara-dpo-7k-binarized
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inference:
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parameters:
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temperature: 0.7
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model-index:
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- name: zephyr-orpo-141b-A35b-v0.1
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results: []
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---
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# mlx-community/zephyr-orpo-141b-A35b-v0.1-8bit
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This model was converted to MLX format from [`HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1`]() using mlx-lm version **0.9.0**.
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Refer to the [original model card](https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1) for more details on the model.
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("mlx-community/zephyr-orpo-141b-A35b-v0.1-8bit")
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response = generate(model, tokenizer, prompt="hello", verbose=True)
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```
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{
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"add_cross_attention": false,
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_dropout": 0.0,
|
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"bad_words_ids": null,
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"begin_suppress_tokens": null,
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"bos_token_id": 1,
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"chunk_size_feed_forward": 0,
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"cross_attention_hidden_size": null,
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"decoder_start_token_id": null,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"early_stopping": false,
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"encoder_no_repeat_ngram_size": 0,
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"eos_token_id": 2,
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"exponential_decay_length_penalty": null,
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"finetuning_task": null,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"hidden_act": "silu",
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"hidden_size": 6144,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"initializer_range": 0.02,
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"intermediate_size": 16384,
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"is_decoder": false,
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"is_encoder_decoder": false,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"length_penalty": 1.0,
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"max_length": 20,
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"max_position_embeddings": 65536,
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"min_length": 0,
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"model_type": "mixtral",
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"no_repeat_ngram_size": 0,
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"num_attention_heads": 48,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 56,
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"num_key_value_heads": 8,
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"num_local_experts": 8,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"output_router_logits": false,
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"output_scores": false,
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"pad_token_id": null,
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"prefix": null,
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"problem_type": null,
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"pruned_heads": {},
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"quantization": {
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"group_size": 64,
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"bits": 8
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},
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"remove_invalid_values": false,
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"repetition_penalty": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000,
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"router_aux_loss_coef": 0.001,
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"router_jitter_noise": 0.0,
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"sep_token_id": null,
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"sliding_window": null,
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"suppress_tokens": null,
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"task_specific_params": null,
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"temperature": 1.0,
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"tf_legacy_loss": false,
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"tie_encoder_decoder": false,
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"tie_word_embeddings": false,
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"tokenizer_class": null,
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"top_k": 50,
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"top_p": 1.0,
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"torch_dtype": "bfloat16",
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"torchscript": false,
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"transformers_version": "4.39.3",
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"typical_p": 1.0,
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"use_bfloat16": false,
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"use_cache": true,
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"vocab_size": 32000
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}
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"chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
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