MaziyarPanahi

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Meta-Llama-3-70B-Instruct-GGUF

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you just load the part 00001, Llama.cpp or any other library will load the rest automatically. https://github.com/ggerganov/llama.cpp/discussions/6404

When I try to load I get this warning: UserWarning: huggingface_hub cache-system uses symlinks by default to efficiently store duplicated files but your machine does not support them and then loading fails:

• llama_load_model_from_file: failed to load model
• pydantic.v1.error_wrappers.ValidationError: 1 validation error for LlamaCpp
  I also use LlamaCpp which is the Langchain integration. Do I need to set specific parameters, additionally?

could you please share how you are using the model?

huggingface-cli download MaziyarPanahi/Meta-Llama-3-70B-Instruct-GGUF --local-dir . --include '*Q6_K*gguf'

Once all the Q6 models where downloaded, locate the directory and point to the first split:

./llama.cpp/main -m ./path_to_q6/Meta-Llama-3-70B-Instruct.Q6_K-00001-of-00002.gguf -r '<|eot_id|>' --in-prefix "\n<|start_header_id|>user<|end_header_id|>\n\n" --in-suffix "<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" -p "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful, smart, kind, and efficient AI assistant. You always fulfill the user's requests to the best of your ability.<|eot_id|>\n<|start_header_id|>user<|end_header_id|>\n\nHi! How are you?<|eot_id|>\n<|start_header_id|>assistant<|end_header_id|>\n\n" -n 1024

from huggingface_hub import hf_hub_download

from langchain_community.llms import LlamaCpp

model_path = hf_hub_download(
    repo_id=model_id,
    filename=model_basename,
    resume_download=True,
    cache_dir=args.models_dir,
)

kwargs = {
    "model_path": model_path,
    "n_ctx": args.max_new_tokens,
    "max_tokens": args.max_new_tokens,
    "n_batch": args.n_batch,
    "rope_freq_scale": args.rope_freq_scale,
    "stop": ["<|eot_id|>"],
}

if args.device.lower() == "mps":
    kwargs["n_gpu_layers"] = 1
if args.device.lower() == "cuda":
    kwargs["n_gpu_layers"] = args.num_gpu_layers  # set this based on your GPU

print("KWARGS:", kwargs)
return LlamaCpp(**kwargs)

where:
MODEL_ID_LLAMA3: "MaziyarPanahi/Meta-Llama-3-70B-Instruct-GGUF"
MODEL_BASENAME_LLAMA3: "Meta-Llama-3-70B-Instruct.Q6_K-00001-of-00002.gguf"

Sorry I don't know which version of llama.cpp the langchian_community is using. The Llama.cpp itself and all the other libraries on top of it works without any issue. You can follow the link i shared to merge the splits back if langchain doesn't support split gguf.

I have figured it out. Instead of hf_hub_download which only allows one file I use snapshot_download where I set pattern for the file format:

from huggingface_hub import snapshot_download
snapshot_download(
    repo_id=model_id,
    cache_dir=args.models_dir,
    allow_patterns=["*Q6_K*gguf"]

Thanks for sharing. I think this works as well in the README: huggingface-cli download MaziyarPanahi/Meta-Llama-3-70B-Instruct-GGUF --local-dir . --include 'Q2_Kgguf'