TriLMs unpacked to FP16 - compatible with any implementation supporting LLaMa architecture in huggingface's transformers format.
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QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.
QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.
FP16 LLMs with LLaMa architecture, trained on same 300B tokens as TriLMs.
QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.
QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.
TriLMs unpacked to FP16 - compatible with any implementation supporting LLaMa architecture in huggingface's transformers format.
FP16 LLMs with LLaMa architecture, trained on same 300B tokens as TriLMs.
QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.
QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.
QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.
QuantLMs, unpacked to FP16 format - compatible with FP16 GEMMs. After unpacking, QuantLMs have the same architecture as LLaMa.