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+ ---
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+ license: apache-2.0
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+ widget:
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+ - example_title: Yi-34B-Chat
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+ text: hi
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+ output:
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+ text: ' Hello! How can I assist you today?'
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+ - example_title: Yi-34B
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+ text: There's a place where time stands still. A place of breath taking wonder,
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+ but also
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+ output:
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+ text: ' an eerie sense that something is just not right…
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+
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+ Between the two worlds lies The Forgotten Kingdom - home to creatures long since
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+ thought extinct and ancient magic so strong it defies belief! Only here can
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+ you find what has been lost for centuries: An Elixir Of Life which will restore
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+ youth and vitality if only those who seek its power are brave enough to face
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+ up against all manner of dangers lurking in this mysterious land! But beware;
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+ some say there may even exist powerful entities beyond our comprehension whose
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+ intentions towards humanity remain unclear at best ---- they might want nothing
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+ more than destruction itself rather then anything else from their quest after
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+ immortality (and maybe someone should tell them about modern medicine)? In any
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+ event though – one thing remains true regardless : whether or not success comes
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+ easy depends entirely upon how much effort we put into conquering whatever challenges
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+ lie ahead along with having faith deep down inside ourselves too ;) So let’s
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+ get started now shall We?'
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+ pipeline_tag: text-generation
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+ tags:
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+ - mlx
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+ base_model: 01-ai/Yi-34B-200K
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+ ---
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+
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+ # Fmuaddib/Yi-34B-200K-mlx-6Bit
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+
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+ The Model [Fmuaddib/Yi-34B-200K-mlx-6Bit](https://huggingface.co/Fmuaddib/Yi-34B-200K-mlx-6Bit) was converted to MLX format from [01-ai/Yi-34B-200K](https://huggingface.co/01-ai/Yi-34B-200K) using mlx-lm version **0.21.5**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("Fmuaddib/Yi-34B-200K-mlx-6Bit")
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+
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+ prompt="hello"
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+
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+ if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
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+ messages = [{"role": "user", "content": prompt}]
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+ prompt = tokenizer.apply_chat_template(
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+ messages, tokenize=False, add_generation_prompt=True
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+ )
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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```