Add plamo-2-1b model

[mitmul]

This PR adds the latest SLM from Preferred Networks, PLaMo-2-1B.

Currently it can successfully generate correct responses when I use the following code:

import mlx.core as mx
from mlx_lm.utils import load
from mlx_lm.models import cache

model, tokenizer = load(
    "../plamo-2-1b-mlx",
    tokenizer_config={
        "trust_remote_code": True,
    },
    model_config={
        "trust_remote_code": True,
    },
)

user_input = "美味しいカレーの作り方のレシピを紹介します。"

input_ids = tokenizer.encode(user_input)
input_ids = mx.array(input_ids, dtype=mx.int64)

y = input_ids
prompt_cache = cache.make_prompt_cache(model)

for _ in range(100):
    logits = model(inputs=y[None], cache=prompt_cache)
    logits = logits[:, -1, :]
    logprobs = logits - mx.logsumexp(logits, keepdims=True)
    next_y = mx.argmax(logprobs, axis=-1)

    response = tokenizer.decode(next_y.item())
    print(response, end="")
    y = mx.concat([y, mx.array(next_y)])

However, when I run the following command from my terminal:

python -m mlx_lm.generate \
--model plamo-2-1b-mlx \
--prompt '美味しいカレーの作り方のレシピを紹介します。' \
--verbose true \
--max-tokens 128 \
--ignore-chat-template

the outputs are totally corrupted.
Now I'm investigating the cause of why mlx_lm.generate doesn't work for this model.
I guess it relates to the cache implementation in this code.

[mitmul]

I found a bug in my code that performs causal-conv1d update, which was related to the difference between the channel-first conv1d in torch and channel-last conv1d in MLX. I fixed it and confirmed that it runs properly as expected, so I changed this PR's state to review-ready 🙏